alt.hn

7/21/2026 at 3:17:16 PM

Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

 https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-6-flash-3-5-flash-lite-3-5-flash-cyber/

by logickkk1

7/21/2026 at 3:52:39 PM

I wonder how big the Pro model is that Google is using behind the scenes to train these smaller ones.

Going on baseless speculation, the lack of accompanying pro models with these flash releases either means: 1) the model is too big to be economical, 2) google doesn't have the compute to serve the big model, 3) their big model has too many alignment issues to serve to the public.

edit: looks like benchmarks are up on https://artificialanalysis.ai/models/gemini-3-6-flash. It's solidly middle-of-pack. However, if you want to be most fair to flash, look at the intelligence vs time per task and intelligence vs outputspeed benchmarks. This is a very fast model.

edit 2: I use antigravity from time to time and in my experience, 3.5 flash is an underrated model, so long as you know what it's good for. It's very good at frontend (much better than gpt 5.5) and it's fast, so it's a great tool for iteration. I expect 3.6 to be no different.

by postalcoder

7/21/2026 at 4:15:16 PM

It's also very possible that they know their big model underperforms chatgpt 5.6 and fable by too much, so they are focusing on what they can get wins in like speed instead.

by Tenoke

7/21/2026 at 9:27:10 PM

That's the only explanation that makes sense. If it was frontier but cost or compute were limiting factors, they'd release it at an obscene price for the bragging rights. Google doesn't care that much about alignment, and I don't think it's likely to be significantly different than 3.5 anyway. The only reason it would need to be soft-canceled is if it's terrible, and has to end up in a ditch like Llama 4 to avoid shareholder panic.

by Miraste

7/21/2026 at 10:21:34 PM

3.5 pro was clearly a miss. It should have been in prod mid may, not MIA in late July. The brain drain at deep mind is a clear indicator that the people who know the most think that they can’t stay at the frontier.

Antigravity NEEDED to be game-changing. Without the stream of data that Claude, Codex, and Cursor enjoy there is little chance of getting an effective reinforcement learning loop. For the first time in its history, GOOG is at a meaningful data disadvantage, and apparently a cultural one as well.

by reilly3000

7/21/2026 at 5:57:01 PM

That and/or the business case isn’t as clear when serving enormous models? You’re constantly stuck in a red queen’s race where your profitability window is increasingly measured in weeks because the Chinese are right behind you.

For small models (which are probably distilled from their big ones) you can serve them economically all the time and not hemorrhage money.

by janalsncm

7/21/2026 at 10:06:12 PM

> For small models (which are probably distilled from their big ones) you can serve them economically all the time and not hemorrhage money.

For smaller models, you're competing with DeepSeek V4 Flash. (Which I think is a 284B A13B?) Subjectively, this feels about as smart as Sonnet 4.5, give or take. And it costs $0.09/$0.18 on Open Router, compared to $1/$5 for the latest Claude Haiku. See https://openrouter.ai/deepseek/deepseek-v4-flash#providers The developer antirez of Redis fame uses this as a local coding model.

DeepSeek did some extremely clever research on hybrid attention to get the prices that low, reducing per-user context cache sizes dramatically.

So, no, when it comes to low-price models, the US models probably can't sustain their current margins there, either.

by ekidd

7/21/2026 at 8:07:48 PM

The Chinese have been right behind OpenAI and Anthropic for ~18 months now.

DeepSeek didn't do to OpenAI and Anthropic what nearly everybody claimed they would.

Every single person on HN that loudly proclaimed the end was nigh for GPT & Co. due to DeepSeek, was wrong. They were humiliatingly wrong, and they'll never own up to it. The reason those people were so very wrong, is the same exact reason the Kimi crowd is wrong now. And it's very obvious that they're wrong, but they have intense emotional blinders on. Their thinking process is hyper emotionalism: they want a certain outcome, regardless of if reality aligns to that or not. They're making emotional wishes about how they want things to turn out, and pretending those magic wishes are grounded in reason.

It takes enormous resources to run something equivalent to GPT 5.6 or Fable. Nobody can or wants to do that outside of very limited situations - if you can just reasonably pay as you go instead. As it turns out, you can just pay as you go with GPT and Fable. Their businesses have gotten radically larger since DeepSeek launched. Get it yet?

Domestic China is the only very large audience for their own models, so long as OpenAI and Anthropic stay top tier.

All the hype online from the forums about Kimi, is worthless: those people hyping it can't even come close to running it locally, which is the fantasy. So why are they hyping it? Why did they hype DeepSeek just the same, and learn nothing from its total failure to actually take down OpenAI and Anthropic? Rhetorical questions with obvious answers.

Kimi poses zero actual threat to OpenAI and Anthropic. Those companies will continue to pile up the subscriptions and API usage. Check out GPT's subscriber base today vs when DeepSeek launched. Get it yet? When Model X launches out of China in a year, we'll have this same conversations all over again, and the hypsters will have learned nothing.

While the Kimi fawning is endless, OpenAI will just keep piling up subscriber counts, and Anthropic will keep piling up API usage. Then OpenAI is going to staple a gigantic ad system onto GPT. China can't compete in the model-as-a-service business globally, for the exact same reason they failed so miserably to compete in search globally.

by adventured

7/21/2026 at 8:27:23 PM

> Domestic China is the only very large audience for their own models

I don't think so. US models are very expensive, and not available in every country. I am not willing to pay $50/1M tokens for writing my pet projects.

by codedokode

7/21/2026 at 9:22:16 PM

There are also US based companies like Fireworks serving up the best open weight models with the compliances we need in US enterprise. Depending on the company, they may offer more/different jurisdictions, EU probably needs a Fireworks like company (haven't heard about one, maybe it already exists?)

by verdverm

7/21/2026 at 9:48:16 PM

There is at least doubleword.ai, and there should be others.

by crown421

7/21/2026 at 8:23:33 PM

without any hard data one way or another your comment is worthless. "pile up subscriptions" - based on what? neither company is public. "piling up subscriber counts", "piling up API usage"? cool. how much money are they making? oh you don't know because they're not public.

the reality is one way or another that as long as there exists an alternative that a USA company could serve with the same compute rented from hyperscalers, this represents a threat, even if the extent to which is unknown

by amazingamazing

7/21/2026 at 8:24:49 PM

But what does that mean for Google if their model isn't as good as OpenAI's and Anthropic's?

by Wowfunhappy

7/21/2026 at 9:00:58 PM

Why wouldn't the hyperscalers run these open models since they're much better than OpenAI and Anthropic at operating compute at scale?

I think the reason OpenAI and Anthropic stay ahead in revenues right now is because the models are improving too quickly to reliably compete with them on cost.

But, once model performance reaches a plateau -- they have to at some point, though perhaps years away -- that's when ability to operate compute infrastructure at scale becomes the secret sauce.

The big AI labs are likely safe until models stop improving fast enough to protect them from competition on cost.

This similar pattern has repeated in most technical booms prior to this.

When hard drive technology was improving fast enough that old hard drives were quickly obsolete, IBM could maintain good margins making hard drives. But once hard drives got good enough and advances were slow enough that innovation was not the only factor considered by drive purchasers, commodity hard drives started to take over and IBM had to exit those businesses.

The same is likely to happen once model improvement slows.

by ijidak

7/21/2026 at 9:07:29 PM

You’re absolutely right and it’s heartening to see. I maintain a client with ~every provider you can think of and llama.cpp and it was really tiring the last few days to see people laundering other stuff through Kimi and Qwen. They’re not even open yet, the hype was based on their own blog posts, no one’s actually running these locally, the Qwen Max’s have never been open, Kimi’s API was 1/2 the speed the benchmarks was based on, when it was up, and had 60% downtime before they had to stop accepting new accounts, and their EULAs are “your inputs and outputs are ours.” May being clear-eyed benefit us both in the long run.

by refulgentis

7/21/2026 at 9:27:50 PM

"You’re absolutely right and it’s heartening to see"

Damnit, I usually don't jump to LLM speech patterns, but this opening had me thinking you were a bot. But after checking your profile, I think you pass as human. I wonder when will be the time, this does not work anymore for me. (Creation date is a strong hint, but abandoned accounts can be hijacked)

by lukan

7/21/2026 at 5:21:01 PM

Yes agreed - I wrote this up a while back https://martinalderson.com/posts/whats-going-on-with-gemini/

My view then was they are optimising the models for inference ability on their own hardware AND use cases, which is often speed and time to first token.

They've somehow seemed to end up with terrible compute shortages, which again is surprising given how good Google is at infra deployments AND have their own hardware. From rumors out there they are turning down enterprise deals for Gemini because they don't have the compute.

The problem is they're falling further and further behind on frontier class on coding especially, and since I wrote that article it's got even worse with open weights models undercutting them on price AND intelligence.

by martinald

7/21/2026 at 4:35:24 PM

There was some recent reporting that a July release of the Pro model got pushed back for exactly that reason. Its performance was not good compared to the OpenAI/Anthropic big models. They are having a lot of problems with posttrain.

by mediaman

7/21/2026 at 4:17:14 PM

This is the feeling i get too. Cant produce quality, but can produce something that is super fast...so take the wins where they are.

by verelo

7/21/2026 at 4:51:54 PM

We don't have enough fast models, so I see this as a positive. I just test drove Gemini Flash Lite and it's crazy fast.

by copperx

7/21/2026 at 9:19:46 PM

For a coding LLM specifically, when is fast a good tradeoff for quality?

by dotancohen

7/21/2026 at 9:25:27 PM

I wouldnt say it is, but there are circumstances when speed is helpful. I wouldn't argue that coding is one of them.

by verelo

7/21/2026 at 4:50:03 PM

I personally doubt that.

It would be a shame if they cannot beat Kimi K3 or Qwen3.8 Max, both of which are claimed to be Fable-like. If that is true, it will be [or would be] the first time a major American lab falls behind a Chinese competitor.

by maxloh

7/21/2026 at 8:57:57 PM

Google can't compete with China, neither can Meta. Only two labs in the US can keep chucking billions at the frontier race. Everyone else has a real business to run.

China can keep up because it's cheaper to run a frontier lab there. They also have more researchers and a stronger cultural inclination for this sort of thing. And I guess the business case in China doesn't have to work as well as it does in the US.

by chrsw

7/21/2026 at 6:30:05 PM

> focusing on what they can get wins in like speed instead

Speed as a differentiator has always been Google's thing. They (used to?) show the microseconds it took to query & rank web-scale search results. Chrome, notoriously, focused on speed at the expense of resource use. The very many efforts to efficiently speed up Android & its runtime since its inception, and so on...

> their big model underperforms chatgpt 5.6

Possible but TFA claims:

  We have started our most ambitious pre-training run yet, for Gemini 4 ...

by ignoramous

7/21/2026 at 9:42:02 PM

That sonds like they can't compete with 3.5 or 3.6 so they must increase the model size and are training v4.

by mnicky

7/21/2026 at 7:26:17 PM

I choose fourth option.

4) googles big model just performs worse than K3 and GLM so they choose not to embarass themself.

Like I love Gemini and use it a lot to one-shot whole MR with huge contexts, but its just much worse when its come to tool use and agentic coding.

by SXX

7/21/2026 at 3:59:05 PM

I wonder if the broad use of AI overviews on Google search results is having an impact. Maybe the numbers make it more profitable to use their compute on several billion searches a day rather than selling API access.

by petercooper

7/21/2026 at 4:17:15 PM

I think it's a safe bet that Google seems more interested in making a model that improves Google rather than making a model that improves workers.

Fast, light weight, ok intelligence. Perfect for serving 20B+ prompts per day mostly surrounding banal human things.

OAI and Anthropic's cloud spend can cover the revenue gap, as Google is already capturing a large chunk of those guy's revenue.

by WarmWash

7/21/2026 at 5:48:58 PM

Not to mention internal use cases, such as prediction-related tasks like serving ads.

by bitshiftfaced

7/21/2026 at 4:21:41 PM

The AI mode on Google search is pretty impressive. Helped me figure out what a bunch of stuff I was seeing out the window was while traveling.

by neutronicus

7/21/2026 at 4:58:16 PM

Microsoft also seems to be working in this space. They recently released this:

https://huggingface.co/microsoft/bitnet-embedding-0.6b

It’s a small multilingual embedding model designed for things like search, RAG, and semantic similarity. It supports a fairly large context window and is designed to run efficiently on a CPU in a GPU starved world.

The interesting part is that it builds on BitNet, using ternary weights of -1, 0, and 1 instead of the usual floating-point weights. That should make indexing and searching large amounts of text much cheaper without giving up too much accuracy.

by SadErn

7/21/2026 at 5:26:32 PM

AI overview is just a summarization of the top 2-3 results. Of course at Google scale that will still need a ton of compute, but the requirement for generating an overview is many orders of magnitude lower than asking the same question in Gemini.

by paxys

7/21/2026 at 8:25:16 PM

based off what?

by amazingamazing

7/21/2026 at 8:39:13 PM

vibes (coding)

by butlike

7/21/2026 at 9:16:07 PM

More likely they don't manage to advance benchmarks on the SOTA level anymore. In other words: They can't beat 5.6 nor Fable

by zwaps

7/21/2026 at 10:05:07 PM

2.5 flash was absurdly capable on a cost basis

by joshu

7/21/2026 at 8:53:44 PM

I think it's 2. I frequently get told there's no capacity for Pro and the query is answered by Flash with extended thinking. And tbh it's hard to tell the difference between the two, especially if you're not coding with it.

by rjh29

7/21/2026 at 10:12:09 PM

It's hard to tell the difference because they nerfed Pro to oblivion, it used to be much, much better model (even for non-coding/chat)

by hn8726

7/21/2026 at 4:54:31 PM

It seems like there are some credible rumors that Google is actually winning in terms of actually building models that work and don't lose money- between how they're able to price them, the TPU advantage and their capex advantage (being able to raise debt + just having a lot of cash - well I said not lose money... more like not go bankrupt).

From the outside they look like they're behind in terms of frontier models, but I think they might be the best positioned to not go out of business when the bubble pops.

Also look at the fact that they've been able to deploy AI-assisted search at google scale. It must be another order of magnitude larger (at least) than the model deployments for OpenAI and Anthropic.

Of course unless you're inside Google it's impossible to know for sure.

by awongh

7/21/2026 at 7:02:30 PM

In terms of open models, Gemma 4 beats the pants off everything else to the point that paying for APIs becomes hard to justify. Qwen has the meme-share for coding, but it feels much less well rounded. I have no doubt that Google have both the infrastructure and the expertise to curb stomp everyone else, should they resolve in earnest to do so.

Lest we forget, "Attention is All You Need" came from Google.

by dTal

7/21/2026 at 9:18:15 PM

> "Attention is All You Need" came from Google

It also came directly from the university of Toronto, and the university of Toronto seeded all American frontier labs (including Grok (why do you think they could start so fast))

by lynguist

7/21/2026 at 9:14:04 PM

Interesting, glad to hear. We have gemma4 at work, and I was considering localhosting qwen, but gemma4 is so far behind the Opus and Fable I have at home that I've decided to hold off for another model release.

by scottyah

7/21/2026 at 8:51:01 PM

How long until Gemma 5 hits?

by ishurand4

7/21/2026 at 8:55:48 PM

Are you suggesting Gemma beats GLM 5.2?

by cherryteastain

7/21/2026 at 10:19:19 PM

At 20x the parameter count I should hope GLM beats Gemma! But is it 20x better? Expertise is demonstrated, not by making big models, but by making small ones. Bigger isn't better if you can't run it at all.

by dTal

7/21/2026 at 8:43:56 PM

It's rumored that Gemini 3.5 flash has a >50% margin, and I'd imagine 3.6 flash is even higher.

I do not think OpenAI or Anthropic are actively chasing margins - though, Anthropic is supposed to be profitable on some form of non-GAAP accounting...

I suspect Google isn't really interested in seeing how far it can get dragged into a race of selling dollars for $0.25, and is more interested to see if it can stay in the race selling $0.50 for a dollar - when everyone else is losing or barely breaking even.

by onlyrealcuzzo

7/21/2026 at 9:15:59 PM

It kind of doesn't make sense though, because typically a large org like Google can afford to crush competitors on pricing. They could probably even go toe to toe with chinese model pricing for years without feeling it.

Maybe they don't want to price war with the other labs so they can comfortably maintain healthy margins on selling them compute?

by WarmWash

7/21/2026 at 7:12:04 PM

That "TPU advantage" might be slowing Google down (though likely not as much as their internal bureaucracy).

Porting CUDA-based research, debugging, and overall experimentation speed is likely slower.

The GPU is still king for training.

by deltaqueue

7/21/2026 at 9:09:34 PM

lmao, you know all Anthropic models are trained on TPU right?

by anthonypasq

7/21/2026 at 5:58:25 PM

They basically don't exist in the currently most profitable LLM market (coding).

Yes, subs like codex are heavily subsidized. But API billing has massive margins and that's what enterprises pay.

by redox99

7/21/2026 at 6:26:52 PM

Does it have "massive" margins? Afaik no one has said publicly what margins there are on an API call?

by awongh

7/21/2026 at 8:07:31 PM

"As of October [2025], OpenAI's compute margins reached 70%, up from 52% at the end of 2024 and double the rate in January 2024, [The Information] said, citing a person familiar with the figures."

https://www.bloomberg.com/news/articles/2025-12-21/openai-se...

As for Anthropic, the rumors I remember seeing for their API margins were more like 85-90%, but I don't have a reference at hand for those. But once you know the API is wildly profitable and the subscriptions are roughly break-even and not even a big slice of their income, all of the investment makes a lot more sense.

by SyneRyder

7/21/2026 at 5:08:27 PM

Logan Kilpatrick said on an interview not too long ago that flash 3 and 3.5 are the same pre-train. all gains on top of 3 flash are post-training

by anthonypasq

7/21/2026 at 5:42:40 PM

Maybe, but they said they have “started” the Gemini 4 pretrain. So not having done any significant pretrain in a year or so seems odd to me.

by mchusma

7/21/2026 at 9:21:09 PM

Pre-trains take a huge chunk of your compute offline, incurring both an raw expense (24/7 max power for all training clusters) and an opportunity cost (could have sold excess compute during that time). They also don't come with any great guarantees, as lots of techniques look good on small scale and crumble or plateau once scaled.

by WarmWash

7/21/2026 at 6:08:59 PM

Maybe it's like Meta not releasing the big version of Llama 4 a year or two ago

by ocamoss

7/21/2026 at 4:12:58 PM

I wonder if they waited for the new TPU generation to train a larger base model.

by spyckie2

7/21/2026 at 5:16:43 PM

> the lack of accompanying pro models with these flash releases either means:

Rumors say 4) it didn't perform well, especially in coding so has been delayed

by re-thc

7/21/2026 at 4:11:48 PM

Or perhaps 4) it's outcompeted severely by other models & releasing it would only tarnish their name

by jauntywundrkind

7/21/2026 at 4:11:05 PM

Google somehow managed to snatch defeat from the jaws of success with their AI products.

They literally forced me and my company out of Antigravity by phasing out AI Ultra subscription without any proper product follow-up. Antigravity IDE cannot even have poweruser subscriptions now from Google Workspace an Gemini Enterprise Agent Platform cannot be attached to Antigravity IDE.

Gemini Enterprise Agent Platform has an incredibly abysmal setup process, and if I want to limit spending per-user I have to create projects per user. The fact that you cannot activate Anthropic models on it if the billing still has free credits is almost a joke.

I was a big proponent of Google and Gemini, but they left us reeling with their abrupt product decisions. Forced us to buy $200 subscriptions directly from Anthropic/OpenAI.

by stonewhite

7/21/2026 at 4:17:37 PM

Also a big proponent of Google and Gemini, but their stubbornness in artificially splitting their consumer and enterprise products is extremely annoying. It's pretty weird that I have access to more powerful tools when using my personal Google account compared to my corporate Google Workspace account.

by ngrilly

7/21/2026 at 6:20:21 PM

It's literally the meme of the MS org chart pointing guns at each other.

The GCP team wants their slice, the other team wants some otjer slice, and so on. Everyone wants some crap for their promotion package.

It's no wonder Meta has shit the bed even worse.

It's also why Google still releases actually decent, useful models despite the product being such a hilarious mess. A lot of the time Gemini models have actually been better as production LLMs as part of LLM-based production applications than OpenAI and Anthropic models when it comes to the complete cost:quality:latency:adherence picture. And they still are. We have products in prod that use Gemini because they're better than any other model at the specific task. But we wouldn't dare use it for anything coding related, or even just as productivity tool to rely on, because as a consumer product it's a joke.

by deaux

7/21/2026 at 6:57:28 PM

> The GCP team wants their slice, the other team wants some otjer slice, and so on. Everyone wants some crap for their promotion package.

I got a Google One plan for Gemini, but it came bundled with YT Premium lite, and that somehow made it impossible to renew YT Premium for 30 days. I suspect different teams stealing customers from each other.

by visarga

7/21/2026 at 7:13:46 PM

Google also gave away 1 year Gemini plans with Pixel phones that either did not work at all for existing Google One users or messed up subscriptions by downgrading your account to worse plan, or making your existing paid time shorter if you been on cheaper plan or recently changee countries. Etc.

Like when you try to give Google money they try to squeeze you as much as possible.

At the same time you can get 5 time more limits for free just by registering 10 free Google accounts.

Google subscriptions are one big mess.

by SXX

7/21/2026 at 8:56:06 PM

Exactly my experience. I'm building an AI document-extraction platform, so I had to benchmark a bunch of models — on the cost:quality:latency:adherence picture, flash wins hands down for structured extraction. (Caveat: I've only tested the three US labs and Mistral.). So like u said, totally viable in prod for a relatively static tool. Didn't build the tool suite with gemini, but if you use service mode it currently mainly runs on flash.

Haven't done any serious coding work with the flash models though — but I'm seeing more and more HN comments from people who seem to have picked it up for that in the last couple of months.

by urbsgpw

7/21/2026 at 4:24:44 PM

As someone who's been using Workspace as a personal email account for over a decade this has been such a struggle forever. Just lots of odd limitations to feature sets all over the place.

When they swapped Google Assistant for Gemini as the default voice provider in Android Auto it was so annoying. My wife's non-work space account can get Gemini to do the normal things like play music and what not, but my Workspace one can't do much of anything at all. I can talk about nearly any random topic with it, but getting it to change the playlist, nah, can't help you there.

It's no surprise to me to see them fumble actually supporting a lot of the consumer features of Gemini into Workspace.

by vel0city

7/21/2026 at 4:32:04 PM

I'm in the same situation. But I was shocked discovering it goes both ways: many new Gemini functionalities are only accessible using a consumer account instead of a Workspace account. Also, Gemini is now the only major AI assistant with no support for MCP connectors. Instead of adding this to the core product, like ChatGPT and Claude did, somebody at Google decided that it was smarter to add this fundamental feature to a new product instead: for enterprises this is Gemini Enterprise (which is a product completely different from the Gemini app); for consumers this the new Gemini Spark agent (meaning that you can use MCP within Spark but not within a "non-agentic" chat)... It's clear to me this a symptom of Google shipping their org chart, which is a disaster from a product perspective.

by ngrilly

7/21/2026 at 9:03:53 PM

Microsoft’s Copilot products are a very similar situation where the enterprise and consumer (and GitHub) features only make sense if you think about the org chart. Both companies need stronger top down product thinking.

by snazz

7/21/2026 at 6:32:54 PM

I currently have a free trial AI Pro subscription that will run out next month.

If it weren't for the $10 GCP credit, I'd straight away cancel it. I don't see enough value in Gemini to justify the $20 subscription.

by rescbr

7/21/2026 at 6:45:33 PM

Maybe because they want to train on your data? Workspace AIs are not trained on your corporate data.

by deepsun

7/21/2026 at 5:22:27 PM

i think Google would see more success if they kept the CEO and everyone at the bottom (ie. doesn't manage anyone), and fired everyone else.

Build a whole new management tree - the current people all do a terrible job.

by londons_explore

7/21/2026 at 6:52:14 PM

This drove me bonkers. You can enable play music (etc) in Android Auto for workspace accounts by enabling apps in Gemini. From memory (looking at the settings now, not 100% sure of the magic steps required), but go to admin.google.com, go to 'generative ai', 'gemini app', and 'apps settings', then turn on 'other Google apps'. This lets you play music (and other things) in Android Auto.

by asdf1011

7/21/2026 at 7:38:45 PM

Ah, that could be it. I saw that "Other Google apps" and didn't think that would mean Spotify, but I guess its Android Auto or Google Assistant stuff. I'll give that a try, thanks for the tip.

by vel0city

7/21/2026 at 6:26:24 PM

The entire Google Workspace division is basically Microsoft. I assume they are making a lot of money in order to support their continued disfunction.

by rapind

7/21/2026 at 6:09:21 PM

Also have a workspace as a personal email and ended up getting a personal gmail just to try out the subscriptions before I gave up.

I have multiple anthropic and OpenAI max plans. For Gemini I just use my Cursor $200 a month plan (which also gives me the ability to try grok, conductor, etc)

by peterbell_nyc

7/21/2026 at 7:28:44 PM

Workspace users have different terms of service. This is why new features always launch to consumer first.

by jeffbee

7/21/2026 at 7:29:26 PM

Apparently you cannot turn off using your data as training data with gemini. This is in line with Google's general privacy policies and it's seeming need to create a stasi file on every human.

by scrollop

7/21/2026 at 9:04:38 PM

You can turn it off but it's an all or nothing switch, if you turn it off everything will basically become a temporary chat and all past chats are deleted

by cherryteastain

7/21/2026 at 4:50:33 PM

It's absolute insanity. They have all the resources to have been able to lead from the front with this new technology. They have the products and users to integrate this technology into people's already existing lives. But they keep fumbling.

They're not even benchmarking against other models now, just against themselves - which tells you everything you need to know.

by deanc

7/21/2026 at 5:31:57 PM

What does "leading from the front" get them?

There is absolutely no loyalty when it comes to coding. Nothing could be more common than people threating to jump ship whenever another frontier or open source model comes.

Google is clearly able to keep growing their free and consumer and small business use cases. Unlike corporate coding, we actually have evidence that solo and small businesses can actually see productivity gains.

Anthropic and OpenAI need to stay dancing like mad, because it's their source revenue which underpins their investments.

Why does Google need to shove something at the top at the same desperate cadence? Other than "recursive self improvement leads to AGI" it seems perfectly fine if they push out something dramatically better every year and half.

by msabalau

7/21/2026 at 5:43:42 PM

Unfortunately them giving up coding means they have less traces to train on.

by sarjann

7/21/2026 at 5:37:43 PM

They simply don't have the leadership to lead. And it starts from the top.

by LogicFailsMe

7/21/2026 at 6:18:45 PM

Google promotes people based on shipping features, not making good software. So this breakage means someone is shipping features.

You should be happy for them.

by asdfman123

7/21/2026 at 4:29:25 PM

> Google somehow managed to snatch defeat from the jaws of success

This is still very early days. Who is "on top" has flipped back and forth many times already. The next frontier model release (from whomever) will change things again.

by xnx

7/21/2026 at 5:01:17 PM

I don't think it's that early tbh, agentic coding has ~90% adoption in the US.

Claude Code has largely won individual developer mindshare and has been on top ever since it came out. The benchmarks change, but almost nobody opts to use anything other than Claude IME when I ask them. Enterprise is more competitive since they care about costs and other things, but developers leaning towards Claude puts a thumb on the scales there.

The product doesn't have much lock in, so it is possible to dislodge Claude, and Anthropic could (and some may argue is likely to) just shoot themselves in the foot again and again and again, but Google has never been particularly good at enterprise sales, and they have never actually been at the frontier of intelligence.

I think Google's incentives have mostly about building models for their products, which makes them focus more on the cheap end, and while they need that, it feels like the Innovator's Dilemma is biting them here.

I own a lot of Google stock from working there in the past and have been quite happy about their trajectory up until the last 6 months, but I am getting pretty antsy about their AI story these days.

by Eridrus

7/21/2026 at 5:07:55 PM

> Claude Code has largely won individual developer mindshare and has been on top ever since it came out.

Claude Code's success is not due to the agent but because the model is considered the best for programming and is very heavily subsidized, compared to pay as you go API prices. Consumers and Enterprise are not really locked in and will go where it makes the most sense.

I think they have almost no loyalty by actual developers.

by sdesol

7/21/2026 at 9:14:41 PM

This isn't a perfect survey, but I am a Codex user and most of my employees are pretty stuck in their workflows and were not really interested in trying even when I was saying good things (even pre-Opus 4.8).

When we work trial people, 100% of people ask for Claude rather than Codex or anything else.

When I talk to people at non-AI tech events everyone basically says they use Claude and have not tried an alternative.

Developers writ large are actually not that interested in trying multiple tools, they like customizing their chosen tool and tweaking it forever.

I think developers are as susceptible to brand marketing as everyone else. It's why almost everyone has a Macbook.

by Eridrus

7/21/2026 at 5:14:51 PM

There is no reason to be loyal....There is no moat.

Basically you may choose to drink brand A water bottle, brand B water bottle or tap water. Oh and you might choose the glass water bottle if you use API/Fable.

by Foobar8568

7/21/2026 at 7:09:21 PM

There’s no reason to be loyal, but I guess it’s a bit like any tool, once you get used to how one works why would you change to another? There is some stickiness with an LLM + harness.

by gehsty

7/21/2026 at 5:20:49 PM

Exactly developers can switch to another coding cli and the learning curve is close to zero. Mindshare without switching costs is just a popsicle in the sun.

by lerchmo

7/21/2026 at 5:24:02 PM

Every model has its strengths and weaknesses, being loyal is suboptimal unless you mean being loyal to all of them, which is why cursor would have been well positioned before it got acquired. Now you have to jump through hoops to call Gemini from Claude from codex. Yuck.

by baq

7/21/2026 at 6:02:20 PM

Claude code was one of the first agentic code tool and when openai release models similar in performance they didn't do as well in their tools (now codex)

by kelvinjps10

7/21/2026 at 6:12:27 PM

Claude Code (or any other model/infra/harness co-design) is not subsidized in any normal use of that word. It's trough filling (I've written this up in lurid detail so I'm only going to do it again if anyone cares).

It's not true, it's just a play for margin.

by reinitctxoffset

7/21/2026 at 6:29:06 PM

> I don't think it's that early tbh, agentic coding has ~90% adoption in the US.

Where does that 90% figure come from?

by draebek

7/21/2026 at 6:06:47 PM

Early days or not, Google fucking deleted my IDE and wiped my settings. It took them days to roll out a fix, by which point I had migrated off Antigravity.

by piyh

7/21/2026 at 6:45:25 PM

I guess? Maybe I'm alone here but I don't feel like Fable is particularly more useful than Sonnet most of the time. I feel like the LLMs are good enough for the majority of uses and the hyper expensive premium ones are way into diminishing returns. At this point with Kimi being as good as it is, if they jack up the price any more I'll just go open source.

by noodlescb

7/21/2026 at 4:33:27 PM

I don't think that's true if the reason a company has left the vendor for given model by making it hard to buy. Enterprise IT is enough of a pain in the butt that people will forego the new shiny to avoid the old painful unless it's genuinely better. As you say though, the best frontier model flips regularly, so companies won't go through the hassle of deploying a model if it's proved horrible to do in the past. They'll just skip that model because their current one is fine.

by onion2k

7/21/2026 at 5:02:21 PM

Model quality is only one aspect, the bigger problem is making it work in a fully integrated enterprise platform, and Google has always been lacking when it came to the latter.

At this rate, if Google has a flagship model, you're better off plugging it into a competitor's tooling than hope Google figures out how to use it.

by creshal

7/21/2026 at 4:48:51 PM

Aren’t the subscriptions extremely subsidized and burning cash for Anthropic and OpenAI? A reasonable explanation is they’re simply abstaining from the war of attrition, especially given cheaper comparable models are breaking the illusion that the “frontier of intelligence” has any kind of per token margin.

by repeekad

7/21/2026 at 5:39:11 PM

This is hotly debated and completely unclear. Let's say Anthropics Opus models cost the same to serve as GLM 5.2. GLM 5.2 is 4.4$/MTok while Opus is 5.6 times more expensive. Assume that GLM 5.2 is served at essentially zero margin. Then Anthropic has >80% margin on API pricing. So even if an average person with a subscription pays only 20% of the API price of their usage, Anthropic makes money on subscriptions.

And the real numbers could be better for Anthropic. It's feasible Opus models are actually cheaper to serve than GLM 5.2 because Anthropic have optimized the hell out of inference.

by Certhas

7/21/2026 at 7:00:46 PM

Sure, but then why wouldn’t I use GLM 5.2 at cost or K3?

I guess that’s the big question, will people pay a big margin long term to use their end products / models or will AI tokens be commoditized by many competing players. For coding if I had to pay API costs I’d switch in a heartbeat, enterprise maybe more reluctant?

by repeekad

7/21/2026 at 5:22:04 PM

Makes sense, subsidizing tokens doesn’t seem like a great strategy for a public company.

by lerchmo

7/21/2026 at 5:43:56 PM

And Google alway has a target on its back for antitrust (regardless of claim validity)

by xnx

7/21/2026 at 8:15:35 PM

they're subsidized if you max them out, i'd imagine most users are paying $20 for maybe $2-5 of tokens.

anthropic probably has more customers that use more of their sub, but for open ai where a lot of their subs are consumers through chatgpt.com, they have a lot of free money to work with there

by lanthissa

7/21/2026 at 6:01:21 PM

Possibly, but aren't the tech giants positioned to win a war of attrition? Then again, they're more likely to sit on that cash and wait for the opportune time to buy a frontier lab.

by bdcravens

7/21/2026 at 6:37:43 PM

The subsidizing thing is repeated over and over without proof. Personally, I doubt they're actually subsidized.

by LUmBULtERA

7/21/2026 at 4:32:23 PM

> I was a big proponent of Google and Gemini, but they left us reeling with their abrupt product decisions.

Likewise. This seems like a common feel. I have at least spent $4000 and likely a lot more on Gemini API because I really wanted them to win. I gave up.

by GodelNumbering

7/21/2026 at 5:07:55 PM

I am going to ask a very direct question and only because I am curious.

Why do you care? Why would you spend your own money to a multi trillion dollar company so that they win their own "war" against another multi trillion dollar company?

Please don't get me wrong, I know the question can seem a bit negative, I am really just curious.

by furkansahin

7/21/2026 at 5:16:00 PM

No, it's a fair question. The answer: I believe(d) in Demis Hassabis's vision of AI

Although, I think saying 'wanted them to win' was not accurate. More like, I stuck with them hoping it will get better, and it did get better in many ways, coding was not one of them.

by GodelNumbering

7/21/2026 at 9:01:45 PM

This was exactly my thought process. Coupled with a less idealistic one: mid 2025 if you looked arena ELO scores google seemed to be dominating and I was sure the trend would continue. But they really dropped the ball on coding and tool use.

That being said, controlling android and apple mobile devices is kind of a big deal. And their video models are still top notch.

by urbsgpw

7/21/2026 at 6:10:56 PM

Google Gemini agy is not allowing you to use your token via your own harness. My own harness is far more efficient than agy. They can take a simple stance - if you exceed your token limit they block you - with the 5 hr limit they are already doing this . so there should be no reason to block you from using your own harness - if you are more efficient - you gain - if you are less you lose .

They are not allowing me to hit their endpoints which agy hits - it's frustrating . i tried to hack it with gemini itself. what i love about gemini is it's so encouraging and ready to help you - even against the agy client : ) .

Even though im so frustrated with this - i still love Gemini for some reason ! Most encouraging model in the world!

by nxdmum

7/21/2026 at 5:59:12 PM

i've got to wonder how much of this is intentional, and how much of this is just google being their usual terrible selves at anything consumer-product related.

Google's biggest and most important customer for all this AI stuff is google. Do they actually want other customers, or is having other people use their AI just an annoyance at this point, where we use up compute that they'd rather use internally...

by notatoad

7/21/2026 at 7:24:17 PM

I trust Google to:

* Abruptly ban me and all users from a Google Workspace for no reason whatsoever.

* Abruptly shut down a service.

I'll never give Google my direct money.

by giancarlostoro

7/21/2026 at 7:51:16 PM

Life gets simpler and better as soon as you stop giving money to Google.

It’s so silly that individual people still use their shit. Corporations, I understand - they always choose the most mediocre stacks and tools by default. But why people choose to bring the mediocrity of Google into their lives is beyond me.

by throwuxiytayq

7/21/2026 at 5:05:48 PM

They'll probably be back later. It's very possible they are "saving up" for a much bigger run.

by SkitterKherpi

7/21/2026 at 6:03:04 PM

More likely an acquisition.

by bdcravens

7/21/2026 at 6:17:02 PM

+1 same way vscode killed its usage base and gave it to its fork - cursor

by dainiusse

7/21/2026 at 7:21:52 PM

> they left us reeling with their abrupt product decisions

This is what happens when you put a McKinsey consultant in the role of CEO of an organization where product managers run the asylum instead of engineers.

by ur-whale

7/21/2026 at 6:53:58 PM

Snatching defeat from the jaws of victory is the specialty of product managers.

by ikiris

7/21/2026 at 4:24:37 PM

It's funny that they triggered the infamous "Code Red" moment in OpenAI when the 3-3.1 models came out. I switched to using them for a lot of single-shot LLM calls because they were fast and cheap. Their only area that they were lacking in was agentic/tool calling.

Needless to say 3.5 was a disappointment. Curious to see 3.6.

by ralusek

7/21/2026 at 6:30:16 PM

> Google somehow managed to snatch defeat from the jaws of success with their AI products.

HN lives in a bubble.

I have German/Italian/Polish clients virtually all use Gemini and NotebookLM. Talking insurance, banking, consulting, legal.

The real world doesn't look at pointless benchmarks on writing react tailwind crap, they are already google suite users, get the tools, test them and adopt them, end of story.

It's going to be like with angular, never mentioned on the net, widely used in the real world.

by epolanski

7/21/2026 at 6:40:08 PM

I have friends and family who use Gemini, but entirely because their Pixel phones came with a year of it for free. No other reason, and they will most likely never pay for it.

by LUmBULtERA

7/21/2026 at 4:19:10 PM

They literally forced me and my company out of Antigravity by phasing out AI Ultra subscription without any proper product follow-up

That sounds awful.

For those of us who don't follow the AI hype cycle, what does that have to do with the topic of this thread: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber?

by reaperducer

7/21/2026 at 4:24:05 PM

That's kinda like asking why someone might complain about Chrome's memory usage in a thread about a new version of V8.

by da_chicken

7/21/2026 at 4:22:24 PM

From the posted link: "3.6 Flash: Our workhorse model that delivers better coding, knowledge work, and multimodal performance."

What is Google's recently released AI coding product?

by browningstreet

7/21/2026 at 7:02:25 PM

"Your new models are great, but uh... How exactly am I supposed to use them?"

That is, given a lot of users' contexts, the way they can and the way they want to use these models are increasingly disjoint.

by zhengyi13

7/21/2026 at 5:17:03 PM

You don't see what Google phasing out an AI product subscription has to do with a Google AI product release?

by logicchains

7/21/2026 at 3:31:06 PM

It's a bit disheartening to see no comparison to other models here - and I'm not sure this pushes the curve anywhere. 3.6 flash is more expensive than GLM 5.2 - but seemingly worse, although this post is really light (lite?) on details.

It seemed for a time that Google had finally gotten the ball rolling, but I'm doubting that more and more as time passes. We'll see what happens with 3.5 pro I suppose.

by m_w_

7/21/2026 at 4:52:47 PM

Here, my comparison of 3.6 Flash vs Sol vs Luna vs Terra: https://aibenchy.com/compare/google-gemini-3-6-flash-medium/...

by XCSme

7/21/2026 at 5:50:27 PM

How does your comparison work? It places Gemini 3.6 Flash Medium above GPT 5.6 Sol High and Fable 5 Medium, which makes me skeptical because that... would be making headlines that I'm not seeing right now.

by jdthedisciple

7/21/2026 at 6:03:39 PM

I have created various questions/tests and put the models through the same tests.

I record whether the answers are correct, and the generation stats (costs, latencies, tokens used, etc.).

I have no idea why the Gemini models do so well.

I have recently added new tests, whose sole purpose was to find some cases on which Gemini 3 Flash fails (I don't like cherry-picking models or tests, but I also find it strange Gemini Flash models leading in accuracy). I made a more complex coding/tool-usage test, that I expected it to fail, it did fail it once locally in my debug tests, but when I finalized the test and ran the entire testing suite for all models, somehow Gemini 3 Flash still got it right...

Gemini models are REALLY intelligent (and they are actually my favorite model to use via the chat app to ask questions), but they somehow fail in real-word coding tasks where they have to modify files, check results, debug, etc.

My tests harness provides a lot of mock data, and limits the number of actions a model can choose from. I am starting to think that maybe the models are not bad, just that the coding harness are not optimized for those type of models, and Google doesn't really provide their own "Codex".

by XCSme

7/21/2026 at 6:43:06 PM

Oh, and I've also added weights to different categories, so Coding and Tool usage categories influence the score more. This done both to better account for how most people are being used, and also to reduce Gemini's dominance in general/domain specific knowledge.

So yes, Gemini models are at the top, even if I actually (not proud of it) tried to make tests that actually favour other coding-focused models.

by XCSme

7/21/2026 at 6:40:23 PM

Interesting, well it'd be interesting to check out some individual examples where Gemini beat the others.

Also, would be great if you could add GPT 5.6 Sol XHigh and Fable 5 High as well, just to see if at least those beat Gemini which is currently your #1.

by jdthedisciple

7/21/2026 at 6:49:59 PM

I don't like to divulge tests, but one of them is a chess puzzle.

> would be great if you could add GPT 5.6 Sol XHigh and Fable 5 High as well

I would like too, but I avoided them for several reasons:

1) Cost - this is a hobby project, those models would cost tens of dollars for each benchmark run, multiply this by tens or hundreds of models and ...

2) Time - the high models are already taking a really long answer to respond (5-10minutes per question). I run each question with 3 repeats (run the same test three times), so it would take 30 minutes per test. If I change my tests, methodology, or add a new test, it would take a really long time to run the benchmark. Also, I like having results immediately when a new model is released, now I can post within 30 minutes of a model's release the benchmark results.

3) High reasoning usually does WORSE on most tests - if you look at the leaderboard, it's sometimes counter-intuitive, but models with high or max reasoning usually do worse than medium and low. This is because the questions are quite targeted/direct, and the models overthink the question and miss the solution. Or the long thinking context makes them perform poorly. The generation tasks (SVGs/HTML animation) are usually better with longer reasoning, but short code fixes, trivia questions, puzzles, etc. are answered by low/med reasoning with more accuracy in general

Also, Fable is borderline un-testable, it refuses to answer many questions, so it scores poorly anyway.

Gemini scores 21/22 because it answers all tests, and it does them correctly, consistently. The only failed test is I think because it miscounted the lines in a file, when responding on which line the bug was in a code snippet.

by XCSme

7/21/2026 at 10:19:05 PM

My usage of GLM 5.2 has been defined by slow throughput and flaky providers, in many (definitely not all!) applications a dumber, faster, and more consistent model makes more sense to me.

by Computer0

7/21/2026 at 5:19:33 PM

It’s really surprising. When Apple announced the multi-billion dollar deal with Google to power Apple Intelligence I thought great things were coming. Instead we are getting more and more bad news: delayed Pro models and AI leadership leaving. I wonder if Apple know something the rest of us don’t know or if they are already regretting their decision.

by florakel

7/21/2026 at 6:22:17 PM

Besides Apple apparently making Siri AI model agnostic, the choice to go with Google was almost certainly for practical reasons. Google is a low-risk established player that already has a long work history with Apple. Google also isn't in an existential battle to establish themselves, Gemini still amounts to just another project at Google. There is tangible non-zero risk that either OAI or Anthropic will be gone in 5 years, or will be forced to leave Apple high and dry to save themselves. There is almost no risk Google will be in either such position. And worst case scenario, Google has incredibly deep pockets should Apple pursue a "refund."

by WarmWash

7/21/2026 at 5:46:04 PM

What Apple wants out of Google is Siri that runs at 8gb ram and isn’t a horrible embarrassment that feels like a primitive markov chain. Given how good Gemma 4 is, Google can squeeze some serious performance in small models. Whether they can make bleeding edge models is irrelevant to Apple.

by revolvingthrow

7/21/2026 at 5:55:15 PM

"Siri, please solve the Jacobian conjecture, and also set an alarm for 8am tomorrow"

by zarzavat

7/21/2026 at 8:40:19 PM

Apple isn't counting on their model to be a frontier coding and cowork model. Gemini is perfectly fine for the tasks that new Siri is supposed to be doing.

by winstonp

7/21/2026 at 6:00:03 PM

As someone on the Apple beta.. the model is almost completely irrelevant to the experience. Apple has gone and done Apple things by nerfing the experience so completely that almost any model in the past year would be fine. I still reach for ChatGPT/Claude/Grok constantly instead of the AI toy that Apple calls the new Siri.

by Petersipoi

7/21/2026 at 4:54:22 PM

All the benchmarks I see put it around the capabilities of Opus 4.8 Medium or Sonnet 5 High.

As far as I can tell it's slightly better than GLM 5.2.

by CSMastermind

7/21/2026 at 9:29:38 PM

according to AA it's not better than GLM 5.2 and that's surprising to me

by zwaps

7/21/2026 at 9:59:28 PM

I personally take AA with a giant handful of salt.

by CSMastermind

7/21/2026 at 5:17:58 PM

The one thing I've found google's models to be the best at is proofreading text in non-english languages. Probably because I imagine they have the most training data for it as Google probably has the most complete archive of the internet.

by sczi

7/21/2026 at 3:46:59 PM

> really light (lite?) on

Light. Lite is product marketing seepage.

by dd8601fn

7/21/2026 at 4:00:05 PM

Yeah that’s the joke :p

by crab_galaxy

7/21/2026 at 7:28:57 PM

I've never questioned the word lite before because it's existed my whole life.. So does it make sense? Why does it exist and where does it come from? More than coming from "light".

by kzrdude

7/21/2026 at 4:03:56 PM

Sorry, it went right over my head!

by dd8601fn

7/21/2026 at 7:24:42 PM

> It's a bit disheartening to see no comparison to other models here

Disheartening, but not surprising: the comparison would not be very flattering for Google.

by ur-whale

7/21/2026 at 4:09:59 PM

[dead]

by lopatin

7/21/2026 at 3:36:54 PM

Pricing per million input/output tokens:

2.5 Flash: $0.3 / $2.5

3.0 Flash: $0.5 / $3

3.5 Flash: $1.5 / $9

3.6 Flash: $1.5 / $7.5

---

2.5 Flash-Lite: $0.1 / $0.4

3.1 Flash-Lite: $0.25 / $1.5

3.5 Flash-Lite: $0.3 / $2.5

by primaprashant

7/21/2026 at 10:22:24 PM

I wonder if this is a plateau towards the real pricing of AI, if you layer in gemini-2.0-flash at $0.10 / $0.70 then its a 15x price increase to 3.5/3.6 flash. But it hasnt gone up again which is interesting.

by jeffybefffy519

7/21/2026 at 4:04:40 PM

3.6 Flash would be a great model at 3.0 flash pricing. At this pricing, its thoroughly trounced by about 10 models on cost/performance including Grok 4.5. 3.5 Flash-ite would be a great model at 2.5 flash-lite pricing, as is, its trounced by many models including Deepseek v4 Flash.

As is, they are thoroughly outclassed for most usecases. I will say the one area where i do see Gemini punching above its weight class is in tasks that are effectively "Google this for me" / knowledge stuff. So it does have a role, and I do use it. So while I think Google is still in a strong position overall, they are really stuck as a tier 2 AI player right now with text models. They are tier 1 in bio, images, and video.

by mchusma

7/21/2026 at 4:17:01 PM

Could also be that they are pricing it at levels where they actually make money. Without seeing the behind the scenes compute cost on all of these its hard to really judge.

That being said with any open model we of course do know the total cost (or estimate)

by Melatonic

7/21/2026 at 4:09:49 PM

3.5 Flash was always too expensive for a "flash" model. They marketed it as "near frontier" level, but there are several order-of-magnitude cheaper open models that compete with it.

by SwellJoe

7/21/2026 at 4:50:35 PM

In my tests, 3.6 Flash is NOT more token efficient, so it actually ends up costing more than 3.5 Flash, even with the output price reduction.

EDIT: It less less verbose in final output though, but it reasons more.

I assume the optimization comes when you have long-running tasks with many tool calls, and by reasoning more, it reduces the number of tool calls needed.

by XCSme

7/21/2026 at 3:54:32 PM

Am I off, or does Google have the pricing that varies the most between model generation releases?

by jjice

7/21/2026 at 3:57:03 PM

It seems that they're trying to push up-market, or at least they were.

Given the extremely competitive releases of GLM 5.2 and DeepSeek V4 (both pro and flash), I don't think there'll be appetite for it.

by m_w_

7/21/2026 at 9:04:10 PM

It seems like they're sticking to a static pricing plan that was made when the only relevant competition were the US labs (im not counting deepseek 2025 as serious competition -> glm and then kimi on the other hand, now that's a different story).

by urbsgpw

7/21/2026 at 3:58:03 PM

Pricing often reflects what the vendors (expects) the customer is willing to pay. It seems that Google is still trying to find their niche in the market.

by LaurensBER

7/21/2026 at 9:39:46 PM

2.5 flash was the only reason we were paying four digits a month to Google....

i guess we'll use 3.0 flash but thats going to get replaced too right ?

these flash lite models aren't very reliable or consistent

by zuzululu

7/21/2026 at 4:04:43 PM

Pelicans for 3.6 Flash and 3.5 Flash-Lite (Cyber isn't available to me through the API yet.)

https://tools.simonwillison.net/markdown-svg-renderer#url=ht...

by simonw

7/21/2026 at 4:08:22 PM

I am growing tired of these pelicans posts every time a new model is published. Feels to me like low effort personal brand promotion. Just sharing my 2 cents.

by rednb

7/21/2026 at 4:43:10 PM

You and a few other people, but enough people still appreciate the bit that I'm going to keep doing it.

They're easy enough to skip - click the little "-" icon and you'll collapse the entire sub-thread.

by simonw

7/21/2026 at 4:56:03 PM

+1. First thing I look for in a model announcement thread. I actually came across this one an hour ago and was sad there were no pelicans yet.

It's a decent heuristic because the better models generate better pelicans. That's all. Nobody sane is going to make a bet on a model based on a pelican. But it's cool, it's tradition by now, and it's a semblance of a good first impression for new models.

by underdeserver

7/21/2026 at 6:37:33 PM

I love and appreciate you doing and sharing them, with stats and details.

thank you.

by froh

7/21/2026 at 7:47:44 PM

I love the pelican escapades.

by oaxacaoaxaca

7/21/2026 at 4:50:44 PM

[flagged]

by hypfer

7/21/2026 at 5:02:30 PM

If enough people agreed with you, simonw's top level comment would be grey. It isn't. Not every comment is for every person, that is fine and normal. He didnt hijack a popular thread in here to make his post. He doesnt have a tin can in your face shouting from a soapbox that makes it hard to ignore. Flag or ignore are reasonable options that can be used.

by nickthegreek

7/21/2026 at 5:37:16 PM

People aren't supposed to upvote or downvote posts for these kinds of reasons here. Most people are downvoting far too much on this website, and it leads to significant echo-chamber dynamics that are worse than even reddit. The pelican test continuing to be taken seriously is a great example of that kind of echo chamber.

"He doesn't have a tin can in your face shouting from a soapbox that makes it hard to ignore."

He metaphorically does because people upvote his pelicans to the top and the ensuing comment threads are massive/bloated. Huge amounts of the readership of this website are lurkers who don't even know how to hide these giant posts. Look at how bloated this very thread is right now!

Also, a lot of people unironically are whining about him because of sour grapes. Pay them what Simon is likely making, give them as much mindshare/attention as Simon gets, and they wouldn't be so mad.

Anti-incumbency bias and anti-elitist attitudes are good actually.

by Der_Einzige

7/21/2026 at 7:10:21 PM

> People aren't supposed to upvote or downvote posts for these kinds of reasons here.

Agreed, but scrolling past or hitting - were apparently off the table for the complainers. So flagging was yet another tool in their toolbelt and I bet a powerful one at that. If simonw's pelican posts routinely went dead from flagging, he would not make them. You know that, I know that.

> The pelican test continuing to be taken seriously is a great example of that kind of echo chamber.

You can try and support that argument if you like. But I would implore you to realize that it has been had many times recently and the other side does in fact find value and do not see it that way.

> He metaphorically does because people upvote his pelicans to the top and the ensuing comment threads are massive/bloated.

Users upvote the pelicans because they find it interesting. they arent paid trolls or simonw fanatics.

> Huge amounts of the readership of this website are lurkers who don't even know how to hide these giant posts.

They can learn... it's called hackernews. For those interested, that is what the [-] link is for above the comment. Use it and move on.

by nickthegreek

7/21/2026 at 4:56:44 PM

I did hit a nerve. I don't like being accused of posting comments here for "low effort personal brand promotion" or nefarious financial motives.

by simonw

7/21/2026 at 5:02:47 PM

Well, yeah. No one does.

But, also, as said, you're an industry (and foss!) veteran, so I find it impossible to believe that you haven't had your fair share of baseless bullshit being thrown at you, and with that, you gaining a persona that will not be hit by that, because it clearly knows that it is in fact bullshit.

Unless of course it doesn't really know that with certainty.

As said, I would _love_ to give you the benefit of the doubt, because you might just have a stressful day or whatever, but content marketing is literally your whole thing by now. It is impossible for me to do that with a clean conscience.

Your blog front page currently opens with

> Earlier this month I hosted a fireside chat session at the AI Engineer World’s Fair with Cat Wu and Thariq Shihipar from Anthropic’s Claude Code team.

That is not what "some rando foss maintainer we are morally obligated to be soft with" does.

But I repeat myself.

by hypfer

7/21/2026 at 5:08:50 PM

I'm a professional blogger now. I still also work on open source software. I'm even fine being called an "influencer" (shudder), but I take offense to accusations of unethical behavior.

I think very hard about the ethics of what I'm doing and how I can best use my "platform" (shudder again) in as constructive a way as possible.

by simonw

7/21/2026 at 5:13:14 PM

[flagged]

by hypfer

7/21/2026 at 5:47:24 PM

> Come on man, can you please just stop, take the L and let the subthread die.

I'd rather you do this than him. Chill out, please. The pelican pic is fine.

by TulliusCicero

7/21/2026 at 5:11:15 PM

What do you want from him, seriously? Anyone who follows the scene knows that blogging about AI (and participating in conferences etc.) is what Simon does nowadays.

There's nothing shady here. The disclosure is front and center on his About page on his website.

He's not spamming you. It's one short link, sometimes a link to a first-impressions post. It's interesting and useful for me and the other commenters who keep upvoting his comments. Why are you so antagonistic?

by underdeserver

7/21/2026 at 5:16:20 PM

[dead]

by noopprod

7/21/2026 at 4:45:04 PM

But how else am I supposed to know when we've reached AGI, until I see an absolutely flawless pelican?

All of the pelicans so far have had really weird flaws / quirks so I am always a little interested to see how well these models perform at this task, since I've seen all the past pelicans and have some anchoring.

Seeing a truly flawless pelican would tell me that the model has true visual reasoning capabilities as well as good taste.

by theowaway213456

7/21/2026 at 4:27:13 PM

I think you're underweighting the Pelican test.

Not only does it give you a super easy-to-grok understanding of the model quality just by looking at the image, but when you compare tokens and costs (both input and output), you really get a good, simple COST x QUALITY evaluation across models.

Simon explains it well: https://simonwillison.net/2026/Jul/16/kimi-k3/#what-can-we-l...

Simon, you should put up a summary table page that you update after every release.

by busymichael

7/21/2026 at 4:20:00 PM

I feel the same way. It was fun at first but has gotten tiresome. Does anyone actually use these models to generate SVGs?

by bayganyo

7/21/2026 at 8:00:08 PM

Yes

by mpyne

7/21/2026 at 4:42:18 PM

Yeah I don’t get it. It tells me which model can draw an svg of a pelican riding a bicycle. It does a great job at that and the presentation is good.

But why is this an indication of literally anything else?

by isatty

7/21/2026 at 8:30:19 PM

It is simply a benchmark. It is well known that benchmarks are not meant to apply to every possible task you might perform.

by zymhan

7/21/2026 at 4:16:58 PM

At this point, it's kind of a hackernews thing. Simon posts them as a single comment in the relevant thread. It's okay for this place to have a little bit of a sense of community, and you can just ignore the comment.

by x187463

7/21/2026 at 4:09:39 PM

Its a nice benchmark. Like hearing the ice cream truck on a summer day.

by tomrod

7/21/2026 at 4:12:32 PM

It's both.

I agree to rednb that at this point it feels like rather obvious brand building, but also, I agree with you that some value is in it.

It does not feel all that authentic though, and it's good to react allergically to lack of authenticity. Bad for a lot of business models, but good for humanity.

by hypfer

7/21/2026 at 5:16:01 PM

Sorry mate, but you sound jealous in all these replies that the Pelican domain isn't your gig. The below is as labored as nitpicks ever get:

> It does not feel all that authentic though, and it's good to react allergically to lack of authenticity. Bad for a lot of business models, but good for humanity.

I hope SimonW keeps them coming.

by squidbeak

7/21/2026 at 5:29:15 PM

My ancestors are smiling at me, Imperials. Can you say the same?

by hypfer

7/21/2026 at 4:16:18 PM

More like living next to an ice cream truck car park

by tomashubelbauer

7/21/2026 at 4:16:15 PM

Every parent groans haha

by neutronicus

7/21/2026 at 4:12:15 PM

At this point it does not show anything as models are fine tuned on all kinds of benchmarks.

by risyachka

7/21/2026 at 5:26:59 PM

I thought the Gemini 3.5 Flash Lite response was quite telling myself. I personally like the Pelican SVG test, to me it is still a charming snapshot of model performance anecdata. No one would argue it's rigorous but I don't think it was ever intended to be.

I get people burning out on the pelican SVG test alongside the rest of the AI burnout, but I guess for myself I'm just choosing to keep enjoying it while I still can.

by SoMomentary

7/21/2026 at 4:11:59 PM

Yeah. It's something I can do myself in a couple seconds if I want, also on more varied SVG scenes. If this is going to be a benchmark people turn to I'd like to see more effort put into it than just a one-sentence prompt.

by cayley_graph

7/21/2026 at 5:11:06 PM

Disagree. They're a nice tradition, but besides that, they're a useful way of eyeballing improvements. I realise labs are likely to be training for Pelicans - but if they're all training for them, the differences in the results are as indicative as they were before labs trained for them.

The 3.6 Flash pelican is just about the best I've seen.

by squidbeak

7/21/2026 at 6:11:09 PM

All the models do this well. It's a test that tell us nothing at this point.

by peder

7/21/2026 at 4:16:22 PM

My 2 cents: you don’t have to look at the pelican if you don’t want to.

by FuckButtons

7/21/2026 at 6:12:39 PM

Hard disagree. I love a little bit of whimsy (which I feel the world is lacking more and more everyday) from Simon everytime a new model is announced.

by nullgeo

7/21/2026 at 9:38:11 PM

Your comment reads very pedantic with a hint of jealousy. The pelican and xbox controllers are great ways to see how well it can follow direction dealing with svg a difficult format for LLMs to use and testing their spatial vision awareness.

by zuzululu

7/21/2026 at 4:48:23 PM

Perhaps freshen it up and extend the test by feeding the model the rendered output so it can iterate once. Assuming a multi-modal model.

by magicalhippo

7/21/2026 at 6:12:03 PM

I'm happy for Simon to post what he wants, when he wants. He's earned it.

by andybak

7/21/2026 at 5:38:16 PM

Vibe code an extension that autocollapses any post mentioning pelicans and by simonw?

by EstanislaoStan

7/21/2026 at 5:51:27 PM

I've been close to writing one that will automatically upvote ALL downvoted posts. I'd call it something like Anti-echochamber.HN

by Der_Einzige

7/21/2026 at 5:20:44 PM

I love them. Keep 'em coming.

by BeetleB

7/21/2026 at 8:56:49 PM

It's just how he is. Prior to LLMs he was cramming a datasette link into every thread. Downvote and move on.

by rjh29

7/21/2026 at 5:22:19 PM

Do something instead of complain

by netdur

7/21/2026 at 6:25:51 PM

I find Simon's work informative and entertaining; the last thing he can be accused of is low effort. The Pelicans are just a bit of fun icing on top.

by justinhj

7/21/2026 at 9:49:15 PM

Sending a one sentence prompt to an LLM and posting it to hackernews constantly isn’t low effort? Today I learnt something new

by purple-leafy

7/21/2026 at 6:23:47 PM

I'll split the difference. When it's a blog post there's usually an interesting observation or two, but if it's totally automated? Maybe just do the ones with a post.

by reinitctxoffset

7/21/2026 at 4:15:05 PM

I like seeing the pelicans, it's a tradition.

by GaggiX

7/21/2026 at 4:14:40 PM

Yeah and it's surely in the training data by now. Long past time to stop.

by IshKebab

7/21/2026 at 4:17:01 PM

You say that, and yet 3.5 Flash-Lite produced an SVG without a pelican.

by miloignis

7/21/2026 at 4:15:56 PM

[flagged]

by xyzsparetimexyz

7/21/2026 at 4:35:49 PM

A new model arrives. The pelican, with uncanny commercial instinct, is never far behind.

Sponsored blogs and paid newsletters are after all, notoriously poor at subsisting on silence :)

by bubble_niter

7/21/2026 at 4:44:03 PM

Linking directly to the rendered markdown as opposed to a post on my blog is a poor way to promote my blog.

by simonw

7/21/2026 at 5:46:28 PM

A piece of the frame is missing between pedals and back wheel. The frame of the bike passes through the bird. It also puts a cap on the bird's head, and a fish in it's mouth.

The fish and the cap where always added when I asked an llm to improve it's first attempt.

This continues the trend in LLM progress of better=more stuff

Edit: I wonder if this is a function of the reasoning training, where more tokens/ stuff is rewarded.

by irthomasthomas

7/21/2026 at 8:05:21 PM

You should be banned for your constant spamming of this. Its ridiculous. Every single AI post! Constant personal promotion.

by purple-leafy

7/21/2026 at 8:49:57 PM

3.1 Flash Lite has a better pelican that 3.6?

by ishurand4

7/21/2026 at 5:23:55 PM

Flash-lite did the John Cena Pelican

by algoth1

7/21/2026 at 5:08:15 PM

[dead]

by noopprod

7/21/2026 at 3:53:22 PM

A couple tidbits:

> Beyond today’s releases, Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready.

> We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress.

by primaprashant

7/21/2026 at 4:38:12 PM

While them fixing token bloat on 3.5 Flash is good work. That paragraph was the real highlight.

Hopefully 3.5 Pro is soon, and that Gemini 4 can be here end of year and finally have an updated knowledge cutoff.

by kingstnap

7/21/2026 at 4:07:12 PM

I guess they meant to release Gemini 3.5 Pro shortly after 3.5 Flash, but then Mythos/Fable and later GPT-5.6 came out with higher performance than 3.5 Pro, so the managers decided not to release it.

by cubefox

7/21/2026 at 10:10:03 PM

It's kind of ridiculous how good these are getting. 3.5 Flash lite is pretty comparable to Opus 4.8 (at least for the couple tests I did) while simultaneously being 6x faster and 19x cheaper.

https://fy2zp1ri90.evvl.io/

by michaelbuckbee

7/21/2026 at 3:28:22 PM

It is both less intelligent and more expensive than GLM-5.2, while being closed weight.

by jgbuddy

7/21/2026 at 3:47:24 PM

But they make up for it by shipping it late.

by drob518

7/21/2026 at 4:13:18 PM

It's also got vision and audio. So, the better comparison is any of the other large Chinese open models that are better and cheaper than Gemini Flash.

by SwellJoe

7/21/2026 at 7:46:46 PM

Google's models are always very well spoken and much more pleasant to talk to. And I've used the open weight models a lot, too.

by kzrdude

7/21/2026 at 4:59:10 PM

It's also about 15x faster.

by JacobAsmuth

7/21/2026 at 7:25:32 PM

It's roughly equal on price and intelligence as GLM 5.2 while being ~8x faster.

by jbellis

7/21/2026 at 4:55:35 PM

It’s multimodal though.

by dyauspitr

7/21/2026 at 7:28:16 PM

> It’s multimodal though.

Sure.

And how does that make your day better? I know it does not improve my work in any way shape or form.

I'll take a better coding model that's not multi-modal any time.

If I need an LLM to do images or sound, I'd rather use a dedicated one instead of a jack-of-all-trades-master-of-none model.

by ur-whale

7/21/2026 at 9:52:04 PM

Personally, I often paste screenshots into Claude Code of the application it’s working on. And I’ve even had it work autonomously on something and regularly grab its own screenshots.

Or sometimes I will have tables, charts, or even screenshots of text that I would otherwise have to have another step to OCR or type out.

Multimodal saves me time on a regular basis. Not sure it’s a game changer, but just lets me communicate with the model in all sorts of ways that would be harder otherwise.

by brokencode

7/21/2026 at 4:38:54 PM

It'd be interesting to know how much the Intelligence as a Service angle serves as a value-add in the minds of Google's executives.

You can get decent open-weight models now. That's not difficult. The difficulty is 1) running them and 2) compliance.

My company runs Claude on GCP's Vertex AI solution. We're in the US healthcare IT space, so the models need to be from somewhere that American healthcare agencies and companies have traditionally been okay with sourcing code from - which means the US, Canada, and maybe Europe. The stuff that handles PHI/PII must be in the US. The expense of hosting is more of a PITA than most customers want to go through this early in the technology's lifecycle, and intelligence gains are simply a matter of degree for most business tasks.

In theory, we could find some open-weight model (likely from China) for our development agentic work and host it anywhere you can host AI models. We don't, though, and I think Google, OpenAI/Microsoft, and Anthropic see that as the core of their business.

by lenerdenator

7/21/2026 at 5:46:56 PM

Is that statement based on token price? More and more it seems that $/token hides as much as it reveals. Token efficiency, tokenizer differences, etc. I'm not saying that you are wrong, I am just saying it is becoming a bit more difficult making statements like this without a bit more research.

by SubiculumCode

7/21/2026 at 4:04:36 PM

It's scary relying on Google's models.

I have a very price sensitive workload that used to run on flash 2.5 lite - it's deprecated now.

The replacement 3.1 flash lite is a lot more expensive, but now also has a sunset date.

3.5 flash lite is even more expensive.

So the price is rising and you have no choice but to keep paying more and more.

by swe_dima

7/21/2026 at 4:08:34 PM

I moved directly from 2.5 flash lite to deepseek v4 flash, its already cheaper and if your prompt caching is good you can save so much more money.

by rayboy1995

7/21/2026 at 4:15:52 PM

could you explain how to optimize prompt caching or point to a doc about it?

by binary132

7/21/2026 at 4:27:43 PM

Anything Sam Rose is worth reading: https://ngrok.com/blog/prompt-caching

but the implementation will be up to your provider and harness, for deepseek, they expose some numbers: https://api-docs.deepseek.com/guides/kv_cache/ and Anthropic has a list of actions invalidating your cache: https://platform.claude.com/docs/en/build-with-claude/prompt...

Basically, you avoid anything dynamic: model change, tool change, etc it's also important that your system prompt or main prompt doesn't have non-static data like the date/time/place or someone's name (the person you interact with in a chatbot for example). That should be left to tool call or search.

by NeutralForest

7/21/2026 at 5:20:36 PM

Sam Rose here. Thank you <3

by samwho

7/21/2026 at 5:27:40 PM

The man himself, thank you for the articles =)

by NeutralForest

7/21/2026 at 6:50:06 PM

You are extremely welcome.

by samwho

7/21/2026 at 7:07:26 PM

samwho? samrose.

by insane_dreamer

7/21/2026 at 4:38:29 PM

I just put the varying parameters in a trailer prompt and have them change every time. It doesn’t matter because the cache is prefix keyed. You lose caching for the last 20 tokens or so but that’s not a big deal. Moving it to a tool call makes it too slow (needs full roundtrip).

If you’re constructing the prompt you don’t have to jam everything together you can arrange it appropriately.

by arjie

7/21/2026 at 4:46:00 PM

Yes indeed! Mostly don't put changing data in the beginning or prepend.

by NeutralForest

7/21/2026 at 5:53:31 PM

Not an open source, but I discuss it in my book with examples for OpenAI/Anthropic/Gemini, https://crimede-coder.com/blogposts/2026/LLMsForMortals.

All of the models, you need to have a consistent input to get the cache hit. So if you are chatting with a document, and change the system prompt, it will be a cache miss, even if the rest of the items are all the same. If you even pass in the document in not the same order as the prompts, it will be a cache miss. Or if you add tool calls or structured outputs, it will be a cache miss. (Since those generally go at the beginning of the prompt call, not at the end.)

Most of the time when reading documents from URLs directly it will never cache. (Need to typically pass in the bytes directly, or use the provider document store index.)

Gemini has a 4096 minimum token size with the 3 version models before even getting a cache hit. OpenAI it is lower (1024), and is automatic, but only happens in increments of 124. Anthropic can also get cache hits at 1024 tokens, but you need to explicit ask for it (and pay extra).

Caching by default typically lives for 5 minutes since the last cache hit across providers. But some of them you can ask for longer. AWS for Anthropic models can be tricky with multiple endpoint routing, so can get cache misses if it happens to route to a different endpoint.

by apwheele

7/21/2026 at 4:27:39 PM

That’s part of why, since Firebase, I’ve tried to never depend on Google products for business, especially not GCP.

Features stay in Beta for ages, whatever that actually means, and released ones get deprecated things fast.

Where some of the competitions treats deprecating entire services as "let’s not put it on your frontpage, put deprecation notices all over the doc, and politely ask new users not to start new project with them".

by ElFitz

7/21/2026 at 4:09:46 PM

Just switch the model, its not that much effort tbh. And u can also get a cheaper model than 2.5 lite for the same intelligence

by hagen8

7/21/2026 at 4:34:00 PM

its not always that simple. dropping in a new model is trivial, but highly specific workflows may rely on specific _invisible_ aspects of a model. when that model gets deprecated, the workflow needs to be rebuilt/re-tuned to work with a different model.

google's inability or unwillingness to provide stable timelines for model deprecation makes it risky to build complex workflows using their models

by tacoooooooo

7/21/2026 at 6:20:59 PM

Load-bearing (whoops) quirks were noticeable months back, but haven't most flagship models become predictable and reliable?

by aitchnyu

7/21/2026 at 8:49:35 PM

it does seem to be moving in that direction. There were really specific things (large, complex json outputs) that gemini-2.5 flash was basically the only model that seemed capable of reliably for a long period. gpt-5+ has covered the usecase for us now pretty well but still evals slightly below what 2.5 could do

by tacoooooooo

7/21/2026 at 4:41:12 PM

100% agreed in the same boat right now. Feeling really screwed over by Google rn

by written-beyond

7/21/2026 at 5:45:48 PM

You would be surprised how much of a difference the model makes for certain niche tasks.

For my use case, `gemini-3.1-flash-lite` is ~20% higher accuracy than the next best model of comparable cost (considering both proprietary and open-weight alternatives)

by ActivePattern

7/21/2026 at 6:31:28 PM

Well it is a bit surprising that 3.1 flash-lite could be better than deepseek-v4-pro (cheaper output and way cheaper cache so might cost less for quite a few use cases).

They are not anywhere close according to pretty much every benchmark (even v4-flash is considerably ahead and its way cheaper than flash-lite). Maybe tuning prompts/tools/etc. might be useful?

by wasfgwp

7/21/2026 at 7:42:42 PM

Gemini flash lite family of models currently has the best ratio for price/speed/intelligence for understanding images, no real alternative AFAIK

by swe_dima

7/21/2026 at 6:22:16 PM

"Intelligence" being what, math? Coding? Unfortunately there's a billion use cases for LLMs whose performance is not at all captured by the popular benchmarks they're all trying to maxx.

by deaux

7/21/2026 at 6:33:43 PM

if you are relying on a model for a business process, it should be simple enough to benchmark on that process

by whimsicalism

7/21/2026 at 4:32:04 PM

> So the price is rising and you have no choice but to keep paying more and more.

I presume you can't use deepseek?

by raducu

7/21/2026 at 4:44:05 PM

There are plenty of 3rd party providers hosting deepseek models, if you don't want to use the 1st party API. 3rd party providers are generally slightly more expensive, but still quite cheap compared to other models of similar vintage and size.

by bradfa

7/21/2026 at 5:24:20 PM

sadly it's not multimodal

by karolist

7/21/2026 at 4:56:47 PM

They know that there's big enterprises that will have a strong preference to work with another big enterprise instead of relying on a younger company. At least that's why I think they believe they can do this sort of thing and get away with it.

by Cyclone_

7/21/2026 at 5:00:40 PM

same here. our production workloads was on Gemini for 2 years. seeing Google unilaterally dropping perfectly fine models and charing you 50x more for worse results is not good.

we are switching to Deepseek.

by 5701652400

7/21/2026 at 9:18:26 PM

And somehow, the most annoying is not even the price hike, but it is that is you expect to build a product on any of theirs models, they spend their time being deprecated and you have like to be on the lookup to start from scratch selecting a model and fitting it every year or so... Impossible to have any stability...

by greatgib

7/21/2026 at 5:53:02 PM

I'm running price-sensitive data extraction workloads on flash 2.5 and its still the king when it comes to accuracy + cost, all the gemini 3 variants perform a bit worse and cost a lot more. Low-key freaking out, ngl

by pdntspa

7/21/2026 at 5:33:03 PM

Opencode Go is just the same. Each month I will I can do less. Dont ask me why?

by h2aichat

7/21/2026 at 4:30:48 PM

I felt the same way about openai's text-davinci-002 and code-davinci-002 (gpt-3.5). They were amazing completion models and openai basically dumped them with no equal cost or equal performance replacement. Instead all their models are opaque with no ability to work in completion mode where one actually controls the text input to the model.

These days no company even has completion models where one controls the text input fully. Worthless.

by superkuh

7/21/2026 at 7:23:08 PM

All models are increasing in price. Everything up to now has been subsidized by investors, private and public.

by thinkingtoilet

7/21/2026 at 4:14:04 PM

same I just switched to OpenAI after using flash 2.5 lite for almost everything at our company. We spent thousands just to build this workflow now Google says screw off

by zuzululu

7/21/2026 at 4:58:58 PM

>So the price is rising and you have no choice but to keep paying more and more.

You can also just write code like you did a year or two ago.

by viccis

7/21/2026 at 5:09:39 PM

[flagged]

by anthonypasq

7/21/2026 at 5:14:06 PM

Can you give examples of other things they can do that would be worth paying for?

by Mistletoe

7/21/2026 at 5:39:42 PM

We use it for sentiment analysis of medical data.

by Cyclone_

7/21/2026 at 6:23:57 PM

Is that worth paying for?

by kgwgk

7/21/2026 at 5:42:18 PM

classifying things, grouping things. We use it to help group issues at Sentry.

by STRiDEX

7/21/2026 at 6:31:26 PM

Mostly because the person I was replying to has commented about using it to write code.

If you're using it for other purposes, then I give you permission to ignore my comment; there's no reason to descend into name calling.

by viccis

7/21/2026 at 4:38:09 PM

[dead]

by stiltzkin

7/21/2026 at 3:32:34 PM

No word about updating Jules, which is still stuck on 3.1 Pro. I get that it's probably niche but I've really appreciated basically being able to give directions to Jules on my phone, then reviewing and merging a GitHub PR fifteen minutes later. It's been great for getting some progress in on a few personal projects during my commute when I can't exactly pull out my laptop.

Anyone have any good alternatives?

by b473a

7/21/2026 at 4:26:47 PM

Both Claude and Codex can code in the cloud, it works quite well!

I tested Jules and while the idea is good in theory, I found the model's intelligence to be very lackluster.

by aweb

7/21/2026 at 5:18:36 PM

Shame. I'm on the $20/mo Gemini Pro plan because the 5tb of cloud storage and the youtube premium lite were good enough perks, and my coding complexity needs were light enough for me to overlook Claude or Codex. But Antigravity is working better than Jules and it's basically giving me a taste of what I'm missing and it's harder to justify not trying out the competitors.

by b473a

7/21/2026 at 4:57:47 PM

I do not, however I am curious about Jules support. I didn't know if this was a dead project or not. Seemed really interesting but then I didn't see much development/announcements/discussions around it. Last update from their changelog was as you said 3.1-pro support in March.

by bespokedevelopr

7/21/2026 at 4:50:20 PM

I have no affiliations with the team or product, but Superconductor reminded me of Jules when I tried it a couple of months ago.

It might be overkill features-wise, but there's a free tier and it likely won't be left for dead anytime soon.

by christoff12

7/21/2026 at 3:45:09 PM

If you own a Raspberry Pi or similar: Hermes + Tailscale + iSH over tmux.

by steven_pareto

7/21/2026 at 3:38:15 PM

Claude Code

by haberdasher

7/21/2026 at 6:19:45 PM

Really, what's up with Gemini still not supporting connectors/MCPs/plugins/whatever-they're-called-this-month on web? It makes it a non-starter for any kind of serious use.

by lilytweed

7/21/2026 at 7:29:45 PM

Their naming scheme is confusing. Branding has never been Google's strong suit and their marketing copy is pretty bottom-of-the-barrel[0]. Anthropic has a pretty clear set of models but Gemini decided to rebrand their Flash as Flash Lite (and presumably the future will see a Flash Lite Mini, a Flash Lite Mini Nano and a Flash Lite Mini Nano 3B) which confuses the pricing to high hell.

This plus the Vertex, AI Studio, Gemini, Antigravity. It's honestly too confusing to use. I need to use Gemini just to decide on which platform and which model to consider.

0: Famous Kurian Tweet: "We're announcing Duet AI for Google Workspace will now be Gemini for Google Workspace. Consumers and organizations of all sizes can access Gemini across the Workspace apps they know and love. We're introducing a new offering called Gemini Business, which lets organizations use generative AI in Workspace at a lower price point than Gemini Enterprise, which replaces Duet AI for Workspace Enterprise."

by arjie

7/21/2026 at 3:43:23 PM

The mention of an "ambitious" gemini 4 pre-train signals to me that 3.5 pro is probably a lost cause.

That being said, it seems that Gemini is still the best image analysis model, so hopefully 3.6 flash builds on this even more.

by WarmWash

7/21/2026 at 9:43:19 PM

Gemini 3.5 flash-lite is more expensive than Gemini 3.1 flash-lite. Every upgrade is getting more expensive.

by zacksiri

7/21/2026 at 3:29:25 PM

Wow - Google does not even bother to show benchmarks of these models compared to the frontier and Chinese labs - only against previous versions. I'm not surprised. Having worked there for years it was amazing just how inwardly looking the company is.

by velominati

7/21/2026 at 3:36:02 PM

I have a side business selling custom fingerprint jewelry and I use gemini nano banana to clean up customer submitted fingerprint images. This was a step I used to do by hand at 10 - 15 minutes per image and nano banana is the first model that is able to do the task (it is astonishingly good at it). I can't wait to see what the next nano banana can do, hopefully its released soon.

by doctoboggan

7/21/2026 at 5:47:34 PM

Are your customers clearly informed that you're sending their immutable fingerprints to an AI service?

by cube00

7/21/2026 at 6:44:27 PM

Yes this is extremely unresponsible if so. Fingerprints are legally protected biometric data in most juristictions.

by poisonborz

7/21/2026 at 9:12:53 PM

From my experience, this thing is crazy fast.

Spawn 10 on the same problem and have them debate to reach a consensus, you’ll get Fable-like results but 100x faster.

by brap

7/21/2026 at 8:02:13 PM

Wow, Laguna S 2.1 (released today) just destroys Flash-Lite underly and completely. What a weak and embarrasing release from Google.

by mchusma

7/21/2026 at 3:58:06 PM

Google seems to have anorexia when it comes to model intelligence. They have an internal hard constraint on price per token it seems, and they are trying to squeeze out intelligence with limited compute.

I wonder if there is something with their TPU cycles that makes them want to postpone training a new model. My guess is that they have been on the same base model for 6 months and they may have waited for the next gen TPUs to train Gemini 4, which greatly limits how much intelligence they can increase and forces them to do cost efficiency increases.

by spyckie2

7/21/2026 at 5:54:27 PM

Could it be that they have to serve their models to billions of users?

by JacobAsmuth

7/21/2026 at 7:29:25 PM

> Could it be that they have to serve their models to billions of users?

And how is that different from their competitors exactly?

by ur-whale

7/21/2026 at 7:53:06 PM

[dead]

by inquirerGeneral

7/21/2026 at 5:27:33 PM

I'd guess they did model-hardware codesign but the design ended up limiting the scaling capability of the model (i.e. they overoptimized too soon).

by logicchains

7/21/2026 at 4:24:08 PM

Google Cloud is probably Google Deepminds biggest competitor. Big company kinda bullshit.

by WarmWash

7/21/2026 at 6:57:20 PM

How so?

by platinumrad

7/21/2026 at 8:23:49 PM

Google cloud sells compute out from under Deepmind to other labs. So they basically are in competition with Google cloud for compute.

by WarmWash

7/21/2026 at 3:34:21 PM

Unfortunately says more about how competitive 3.5 pro would be today at the frontier if they forgo it for 3.6 flash.

by dankai

7/21/2026 at 4:24:23 PM

Google has not changed. Following two facts are like tautologies by now.

1. Their AI efforts are very fundamental research oriented. They are really good at it.

2. Their productization sucks. The end products gets little attention compared to competition. It can be canceled at any time. You should never build anything around Google only APIs, AI or not.

by u1hcw9nx

7/21/2026 at 3:43:42 PM

3.5-lite is the real showpiece here; agentic models of this size are a huge value-add for 90% of knowledge work agent tasks

by youssefarizk

7/21/2026 at 7:16:11 PM

In other good news "the model has been trained to minimize refusals for beneficial uses.".

Otherwise, this news feels like a tiny incremental improvement on Gemini Flash series to make it more efficient with token usage, subagent and cost. Nothing big.

Regarding their benchmark scores on CyberGym, I wonder why they didn't compare their 3.5 Flash Cyber model with Fable 5. I mean they included Mythos and GPT-Cyber, so why not Fable 5 too?

They also mentioned Gemini 3.5 Pro is in testing and its about to become available very soon. Another thing maybe worth discussing is the announcement of pre-training Gemini 4. Sadly, not much technical details to discuss on. Many comments in here seem to mostly be about how Google is behind the others, but honestly, is it really worth the investment to be #1 in Artifical Analysis every week?

by Alifatisk

7/21/2026 at 9:18:55 PM

Here's the issue:

GLM 5.2 is better, also cheaper, and almost as fast.

So essentially, a big L for Google. Combine this with them not being able to produce a frontier model this generation... hmm implications

by zwaps

7/21/2026 at 9:23:54 PM

3.6 is roughly 50% faster, which isn't totally insignificant for being marginally more expensive.[1]

[1]artificialanalysis.ai

by WarmWash

7/21/2026 at 9:33:16 PM

Sure, but there's no sota alternative from Google. That's it, and its beaten by GLM 5.2 on every measure except somewhat speed.

I find that quite staggering. GLM is open weights

by zwaps

7/21/2026 at 8:10:32 PM

3.5 Flash-Lite seems available in US region, as was 3.5 Flash; but 3.6 Flash looks Global only so far when pinging. If Google employees are watching, will this issue go away?

by waldrews

7/21/2026 at 8:28:55 PM

Bottom line it looks about on equal footing with GLM 5.2 in terms of both overall intelligence and cost per task, while being significantly faster (in fact it is the fastest model on artificial analysis as of rn [0])

[0] https://artificialanalysis.ai/models/gemini-3-6-flash

by jdthedisciple

7/21/2026 at 3:34:04 PM

Why would 3.6 flash perform a little worse than 3.5 flash on Artificial Analysis Coding Index...

https://artificialanalysis.ai/models/gemini-3-6-flash?intell...

by ConfusedDog

7/21/2026 at 3:38:05 PM

Because AA Coding "Index" consists only of two benchmarks (Terminal-Bench v2.1, SciCode) and generally fails to be meaningfully representative of agentic coding capabilities.

by sosodev

7/21/2026 at 8:53:52 PM

AA coding index has been updated to use DeepSWE, Terminal-Bench v2, and SWE-Atlas-QnA.

by firethunder7

7/21/2026 at 3:42:41 PM

Whats a better option for AA Coding Index?

by Alifatisk

7/21/2026 at 4:34:11 PM

DeepSWE and FrontierCode are more realistic if you read up on what they actually measure. But the most realistic is to try it yourself. Benchmarks can only vaguely represent typical usage, and how you judge the result. Giving the same real task you have to a few models will make you understand them better than chasing benchmarks.

by WASDx

7/21/2026 at 4:09:06 PM

Could be a good tradeoff for the flash model though. 3.5 -> 3.6 is a tiny bit cheaper and maybe faster?

artificialanalysis.ai has it going from 165 tps -> 304 tps. openrouter.ai needs more data but it has it going from ~100 tps -> ~150 tps, though at peak 3.5 has reached 156tps.

by wmedrano

7/21/2026 at 5:58:52 PM

Pelican svg and a near-perfect 3D MacBook at max effort for $0.16, about a fifth of Fable's price.

Fable 5 still wins on detail with no visible errors, but it's close. And this isn't a memorized pelican;

https://playcode.io/blog/macbook-svg-benchmark#gemini-3-6-fl...

by ianberdin

7/21/2026 at 6:10:51 PM

I don't know if it's a rendering error since it looks like your site renders the SVG instead of hosting a static image of it, but the 3.6 macbook looks like an abstract art piece lol, both ff and chrome desktop

by WarmWash

7/21/2026 at 4:18:24 PM

Tons of guardrails, lazy model, super confusing plans, expensive 3.5/3.6 flash and lite and 3.5 pro MiA?

Rough patch for google ai

by revolvingthrow

7/21/2026 at 8:09:19 PM

Spent half an hour just now benchmarking it against my current 3.5 Flash pipeline excited only see it regressed slightly (0.1% - 0.2% at most, for feature extraction work)

Seems like this is mostly a cost play by Google, hoping this doesn't bring 3.5 Flash capabilities to an end of life, and that 3.6 catches up or gets better.

by hmokiguess

7/21/2026 at 7:51:55 PM

I often use Gemini free web chat because it's generally quite good at web search-related questions (apparently it has direct token-level access to the Google Search index) but I noticed in the last two weeks output quality of 3.5 Flash seriously degraded. Maybe they were switching over systems.

by mrandish

7/21/2026 at 7:57:35 PM

Google's Knowledge Graph is a massive advantage no other competitor has. I don't think they've fully utilized its full potential but I don't know if any other company could've built something like Scholar Labs

by culi

7/21/2026 at 9:40:55 PM

Knowledge Graph + automated transcriptions of almost every YouTube video = giant untapped moat of data

by Andrex

7/21/2026 at 3:30:09 PM

I'm more excited for 3.5 pro. Gemini has fallen behind in some areas, but is still one of the best multimodal models.

Has anybody found any models better at image or audio analysis?

by singingtoday

7/21/2026 at 4:54:36 PM

Came here to ask basically this. We use 3.1 Pro internally and it's great.

by ianhawes

7/21/2026 at 6:08:53 PM

I have just tried to switch to 3.6 instead of 3.5 in antigravity and it seems to constantly spit "critical instruction: STOP CALLING TOOLS NOW. YOU MUST WAIT FOR WAKEUP. ". I think I will switch back to 3.5

by sega_sai

7/21/2026 at 6:10:29 PM

Kind of excited about this. 3.5 Flash on Antigravity has surprised me recently on a hobby project. When given opportunity to plan, it can deliver on tasks that would take me a while on my own and generates responses at blazing speeds - compared to what I'm used to at work with Opus 4.8 (granted I don't use Opus 4.8 on my hobby projects so just anecdotal). While with Gemini CLI I would just watch it run in circles and run out of 5h allowance before anything useful is produced (or even approached).

by parasti

7/21/2026 at 3:30:53 PM

It is 17% more token-efficient than 3.5 and performs significantly better in coding and tool usage benchmarks.

It is also cheaper than 3.5:

> This enhanced efficiency is also combined with a lower price than 3.5 Flash. At $1.50/1M input tokens and $7.50/1M output tokens, 3.6 Flash reduces the overall cost per agentic task, making agents more cost-effective to build and run.

by nsbk

7/21/2026 at 3:44:25 PM

I struggle to see any value in this when DeepSeek is still a thing.

by thevinter

7/21/2026 at 10:04:04 PM

It's smarter than DeepSeek v4 Pro (preview) on several benchmarks, like HLE.

by kzrdude

7/21/2026 at 3:46:09 PM

multimodal + latency

by anthonypasq

7/21/2026 at 4:12:08 PM

Proof-of-life release while they figure out how to have a competitive frontier model release. My hunch is they pushed too far in the "omni" model direction, that they made something so ungainly, it wasn't as good for normal tasks.

by xnx

7/21/2026 at 4:25:21 PM

Always happy to see new Gemini releases as IMO Antigravity Pro 16.67/mo plan (Annual) is still the best plan available and have been pretty happy with Antigravity IDE.

If it wasn't for Gemini/Antigravity I'd have to go with a Max Claude plan, as it stands now I can get by with just a Claude Pro plan to get Opus when I need it, whilst using Antigravity as my day-to-day workhorse.

Unfortunately Gemini Flash became too expensive to use as a general purpose model (i.e. for AI features in Apps), luckily there are plenty of cheaper Chinese models to fill that gap now.

by mythz

7/21/2026 at 9:42:35 PM

What's the current outlook on Antigravity IDE vs. 2.0? How long will they begrudgingly keep it going before kicking everyone to 2.0/3.0?

(I actually use a mix of both for some offline projects, nothing serious.)

by Andrex

7/21/2026 at 4:31:40 PM

Why do you think it's the best plan available?

by ValentineC

7/21/2026 at 5:01:01 PM

(Rate limits * capability of the model) / cost

by JacobAsmuth

7/21/2026 at 3:53:19 PM

Feels like they released this to ride the wave of press of GPT-5.6, Kimi K3, and Qwen 3.8. Doesn't feel like Google has much substance with this post except a bump in version and tweaked their pricing.

by parsimo2010

7/21/2026 at 4:44:27 PM

Don't know why are they even pursuing Gemini. Just download the Kimi, call it Kimini and serve it on your GPU. Maybe then train next architecture based on this!

by sagex

7/21/2026 at 4:57:21 PM

Gemini 2.5 Flash-Lite has been my go to for cheap document processing at scale (especially with 50% off batch mode), but they are really boiling the frog with pricing increases with each version:

gemini-2.5-flash-lite: $0.10 input / $0.40 output

gemini-3.1-flash-lite: $0.25 input / $1.50 output

gemini-3.5-flash-lite: $0.30 input / $2.50 output (a 6.25x increase over 2.5!)

Now watch them deprecate Gemini 2.5 Flash-Lite in the coming months...

by JeremyHerrman

7/21/2026 at 5:58:16 PM

How has your experience been with Gemma 4?

by JacobAsmuth

7/21/2026 at 5:30:32 PM

gemma4 is the same price as 2.5-flash-lite, and performs better.

by tjwebbnorfolk

7/21/2026 at 4:06:10 PM

3.6 Flash scores exactly the same as 3.5 Flash on the Artificial Analysis index. Better on some tasks, worse on others. Mostly within what I'd consider the noise window. Looks pretty much indistinguishable from 3.5 Flash, at least on these benchmarks: https://artificialanalysis.ai/models/gemini-3-6-flash

by lambda

7/21/2026 at 4:42:48 PM

Looks like 3.6 Flash is the first model with their newest pretraining run (cutoff date is 2026/03), long after 2.5 series.

by summerlight

7/21/2026 at 5:02:29 PM

For anyone wanting a faster overview: I ran the Gemini 3.6 Flash and 3.5 series release notes through NotebookLM and generated a short video summary. Link: https://www.youtube.com/watch?v=SUFBhvQ2tY4

by vinhnx

7/21/2026 at 5:54:01 PM

LLM reception is truly extreme, even worse than AAA game releases.

Ever frontier lab lived it at least once : missing the frontier by a few months triggers extremly negative reactions, then you take back the lead for 2 weeks, and the hype cycle repeats.

by goldenarm

7/21/2026 at 9:44:35 PM

I spin a mental roulette on whether the reception on a new release will be "OMG best model by far, no one will be able to catch up for months!" or "OMG this is already outdated, RIP company X, they might as well just give up now, there's no coming back from this."

It's quite a fun game. I click into the comments and see if the roulette wheel was right.

by Andrex

7/21/2026 at 4:45:52 PM

IMO Gemini has the best free tier models/app for everyday use. Muse-Spark is perhaps just slightly better, but has none of the connectivity to my GApps (for things like “create a recipe in my Google Docs from this image”).

Plus they are probably running these things on every Google search so saving tokens is a huge win for them.

by thebigspacefuck

7/21/2026 at 5:18:47 PM

Free? Did I misread the pricing details?

by copperx

7/21/2026 at 3:35:10 PM

I deeply wish Google would focus on models like Gemma. Small, powerful, open-weight models you can run on phones or regular computer hardware.

by kilroy123

7/21/2026 at 4:44:47 PM

Gemma 4 was released in April. It's a good series of multimodal models.

by mediaman

7/21/2026 at 4:49:36 PM

gemma 4 thinks joe biden is president

by accountrequired

7/21/2026 at 8:31:07 PM

I asked Gemma 4 E2B, and if you use it as a reasoning model, it will give a better answer (that it doesn't know; it was also using the date information from the prompt.)

by kzrdude

7/21/2026 at 5:53:00 PM

Small open source models shouldn't be used for world knowledge, that's not their purpose.

by mediaman

7/21/2026 at 6:06:12 PM

Why not? Seems like a cop out.

Being able to ask questions to small open models seems.... obviously useful?

by Petersipoi

7/21/2026 at 7:17:08 PM

Because they don't have a lot of parameters to store general Wikipedia knowledge. They're small. Use big models that have high parameter capacity to store general information. Or build a harness around the small model that searches a knowledge base/internet.

Use the right tool for the job. It's like asking why a screwdriver isn't good at sawing wood, or calling C a terrible language because it's hard to make CRUD apps with it.

by mediaman

7/21/2026 at 3:36:30 PM

i mean eventually then will, losing means open source, vertically integrated hardware means you can opensource and win on cost

by lanthissa

7/21/2026 at 5:37:05 PM

I'm a big fan of the Flash-Lite models. They're exceedingly fast and deliver great outputs for high volume use cases where you need to process requests at scale. Can't wait to try the newer version.

by MILP

7/21/2026 at 3:41:11 PM

So 3.6 Flash is a somewhat of an admission that Google miscalculated by charging 3-5x for 3.5 Flash what it did for 3.0 Flash (3x input and output costs plus large token inefficiency changes) despite only modest improvements?

3.5 Flash Lite is only a hair cheaper than 3.0 Flash, but I think 3.0 Flash is a massively more capable model?

by ComputerGuru

7/21/2026 at 3:29:47 PM

It does seem like their releases are getting closer together. I get the feeling they realized they were trying to roll out to their entire ecosystem and now they’re focusing more just directly on the AI model itself. I think give it a little time and they’ll start to be one of the competitors too.

by dvduval

7/21/2026 at 4:57:57 PM

Flash Lite: 0.3/m and 2.5/m

Deepseek Pro: 0.435/m 0.87/m

That's wildly ambitious pricing by Google. You can maybe get away with spicy pricing at the SOTA edge but at the lower tiers everything is a lot more price sensitive.

by Havoc

7/21/2026 at 5:54:57 PM

You need to compare cost per task buddy boy. Cost per token doesn't tell you much when you don't know how many tokens a model will use to accomplish a task

by JacobAsmuth

7/21/2026 at 7:03:42 PM

>boy

Seriously?

by Havoc

7/21/2026 at 3:27:03 PM

"..and in some benchmarks like DeepSWE by Datacurve, we observe up to 65%, all at a lower cost per output token."

"3.6 Flash delivers higher precision with fewer unwanted code edits and reduced execution loops, as seen in DeepSWE (49% vs. 37%)"

So which one is it? 65% or 49%?

by dumberquestions

7/21/2026 at 3:29:58 PM

First sentence is about token efficiency.

by petu

7/21/2026 at 3:32:55 PM

You're right, should've gotten some LLM to summarize it instead of skimming.

by dumberquestions

7/21/2026 at 3:50:40 PM

Or you could have read it more closely before posting a comment saying it didn't make sense. You know, the old school way.

by semilin

7/21/2026 at 4:09:14 PM

If I'm going to read it wrong might as well have an LLM to blame.

by dumberquestions

7/21/2026 at 4:20:02 PM

I was expecting 3.6 Pro. It's been so long since the last Pro model...

by XCSme

7/21/2026 at 5:08:27 PM

They are working on coming up with a better code name. You know, something like ”Fable” or ”Sol”, gotta have one these days. Personally I think they should go with “Mafia”. How cool would that sound? 3.6 Mafia.

by thebigspacefuck

7/21/2026 at 7:54:38 PM

3.6 Gangsta Pro

by dpacmittal

7/21/2026 at 3:36:18 PM

Are they comparing 3.6 Flash to 5.6 Luna and losing? That's ruff.

by pietz

7/21/2026 at 3:47:03 PM

Why wouldn't they? Luna isn't a Flash model. OpenAI hasn't released a flash-equivalent model since gpt-oss-120b.

by polski-g

7/21/2026 at 4:25:50 PM

Did you ask me a question and then answered it yourself in the very next sentence?

Anyway, given that both Gemini and OpenAI have 3 sizes of models, one would think Google compares their medium size to OpenAIs.

by pietz

7/21/2026 at 7:57:40 PM

Nice to see that it's cheaper than 3.5

by 1saadcodes

7/21/2026 at 4:12:37 PM

I read this as a soft let down to not expect too much from 3.5 Pro.

> We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress.

by Gecko4072

7/21/2026 at 3:27:02 PM

The benchmarks are not particularly impressive. I suppose they needed to release something since the long pause. But not clear why would I use it now.

by yanis_t

7/21/2026 at 4:49:45 PM

I have liked using their consumer products but they don't make it easy, that's for sure.

by TheAtomic

7/21/2026 at 3:34:31 PM

"We made 3.6/4 Pro, but it sucks, so this is the distilled model" vibes.

by catigula

7/21/2026 at 3:49:34 PM

That’s the fear.

by drob518

7/21/2026 at 4:58:02 PM

Glad to see the price is going down but it's still too high for a "fast" model

by spstoyanov

7/21/2026 at 4:00:12 PM

A lot of disappointment here in the comments, but models like these aren't meant to compete with the likes of Fable or GPT 5.6.

I use 3.1 Flash Lite regularly to classify listings on eCommerce websites. It's great for this task - fast, cheap and accurate.

In fact, it was the single best model we tried in terms of the speed vs accuracy vs price tradeoffs - including the Chinese models.

Of course, 3.5 Flash was more accurate but the 5x cost increase couldn't be justified.

3.5 Flash Lite sounds like it could be a strict upgrade for our use case, without a significant increase in costs or drop in speed.

It's not GPT-6 but it's not trying to be. It's a completely different tool and great at what it does.

by AussieWog93

7/21/2026 at 3:34:49 PM

Pretty underwhelming, as expected honestly. I don't want to know what morale is like at DeepMind right now.

by mfkrause

7/21/2026 at 3:48:40 PM

Especially when Google owns 15% of anthropic and serves them compute. Double especially when your boss (Hassibis) is also an early investor in Anthropic. Hell his NW might be more Anthropic than Google.

by WarmWash

7/21/2026 at 3:46:08 PM

Yep, agreed. They still are not releasing anything frontier-class (Gemini Pro) at this point. Feels to me that they keep getting scooped by others (e.g. Kimi 3) and then are retrenching.

by drob518

7/21/2026 at 4:09:21 PM

So about the same “intelligence” as Muse Spark 1.1 but 2x faster and about 2x as expensive.

by metahost

7/21/2026 at 4:43:59 PM

tl;dr: 3.6 flash is a bit smarter than 3.5 flash, but also a bit more expensive.

My results [0] put Gemini 3.6 Flash at the top.

3.6 Flash high has same $1.5 input price as 3.5 Flash, but output is cheaper from $9.0 to $7.5.

Google said 3.6 Flash is more token efficient, but in my tests it's actually LESS token efficient[1] than 3.5 Flash, so despite the output price reduction, it still costs more.

[0]: https://aibenchy.com/compare/google-gemini-3-6-flash-medium/...

[1]: https://aibenchy.com/compare/google-gemini-3-6-flash-high/go...

by XCSme

7/21/2026 at 4:57:29 PM

the real product is the naming confusion we made along the way. Gemini 3.6 Flash, 3.5 Flash-Lite, 3.5 Flash Cyber — at this point even the model cards need a model to explain them

by luciana1u

7/21/2026 at 3:43:44 PM

Google is walking backwards, with such a pile of cash in pocket, i feel they are doomed.

by sreekanth850

7/21/2026 at 4:33:16 PM

Models are expensive and low performance. On top of that they make you jump through hoops to even use these models without being throttled even for the weaker models. The only reason we are using them is credits. As soon as credits run out we are switching immediately.

by vlad_recomply

7/21/2026 at 4:18:50 PM

Haven't been excited for a Gemini release since December. Wild to see.

by gabriel-uribe

7/21/2026 at 4:55:28 PM

quite a good model, the speed/price/quality ration is a new golden intersection for me, not sure if its as good as grok 4.5 but quite fast/capable model.

by maxdo

7/21/2026 at 3:57:08 PM

I'm going to get downvoted/flagged but I feel like we need a new type of "Show HN/Tell HN" etc for "New AI Model Available".

Front page is tedious these days.

by m4tthumphrey

7/21/2026 at 4:05:19 PM

If you refresh the Home page, once a day. The top post will likely be 'New AI Model Available '

by tremarley

7/21/2026 at 7:03:08 PM

> I'm going to get downvoted/flagged but [...]

Why do you care that much? Just say it. You're letting an imaginary score determine if you should express your suggestion for improvement. That's a bit wild.

by Alifatisk

7/21/2026 at 8:15:15 PM

No I'm not, I expressed it...

I prefaced it with that to simply say I knew it'd be an unpopular opinion.

by m4tthumphrey

7/21/2026 at 4:21:48 PM

Not good enough for high-end, not cheap enough to be for low-end. Next!

by baalimago

7/21/2026 at 6:24:04 PM

I have no skin in this game and this comment will be gray in a few minutes BUT a friendly reminder that these types of threads are astroturfed heavily by competitor labs and any info should be taken with a massive grain of salt.

by vrosas

7/21/2026 at 5:14:42 PM

It feels like AI is going to be the end of Google. The post-Schmidt company culture cannot produce consistent, consumer-friendly products that any sane person would want to use consistently.

by speak_plainly

7/21/2026 at 6:00:20 PM

never tried gemini for coding, but this news seems to be compelling, i would definitely give it a try

by Arshad-Talpur

7/21/2026 at 5:30:57 PM

"The model will be exclusively available to governments and trusted partners via CodeMender soon as part of a limited-access pilot program"

we are stealing plutocracy from the jaws of emancipation.

i don't want to live in a world where abundance is guarded and shared among politicians and cronies, whilst the rest are left to rot.

by lukewarm707

7/21/2026 at 5:16:11 PM

no actual cyber model release, useless

by fuomag9

7/21/2026 at 4:11:54 PM

Specific to task these can be huge plus point.

by ansuman441

7/21/2026 at 5:52:20 PM

If only I could use Pi.

by imagetic

7/21/2026 at 8:39:33 PM

Well, you can use the google models from Pi. Go to aistudio.google.com and set up an API key. There is a free quota, it's relatively large for the Flash Lite models.

...and last time I looked the limits were more generous for Gemma 4 there, but they have been tightened a bit. That's how it goes, always changing.

by kzrdude

7/21/2026 at 4:41:15 PM

I remember back when Gemini looked like it was the best model that this comment section was full of confident predictions that Google had "won" and that no one would ever catch up with them again. The most embarassing part is that I kinda believed them.

by QuesnayJr

7/21/2026 at 7:23:21 PM

Why exactly are they announcing these completely milquetoast models ?

I'd be low-keying the release if anything, given how lame they are compared to their competition.

What am I missing?

by ur-whale

7/21/2026 at 6:44:49 PM

Plugged 3.5 Flash Lite into an existing agent harness that was previously using 3.1 Flash Lite and this shit just does not work. It's not following instructions and is not producing the correct tool calls.

by lwansbrough

7/21/2026 at 5:02:00 PM

if only DeepSeeek supported vision, would never use Gemini.

by 5701652400

7/21/2026 at 4:08:05 PM

I think it’s safe to say Google seems a bit out of the top AI competition now. The “cyber” stuff also starts to become laughable with open models providing the full power without the crap Anthropic, Google, OpenAI are trying to frontload on you(I.e you are not allowed to develop/review a login system, pay a special cyber operation team to do it for you). They really deserve to become irrelevant in the future of AI.

by theplumber

7/21/2026 at 3:46:18 PM

The silence is deafening.

Google watches over the last few months a flat out assault on the Pareto curve from American and Chinese companies. Release after release pushing the boundaries of frontier intelligence and price/performance.

And the response from arguably the biggest AI research labs in the world by headcount is Flash 3.6.

What do you do when you are given essentially unlimited resources and still find yourself falling behind?

by WhitneyLand

7/21/2026 at 4:08:01 PM

Start your own openrouter.

by ece

7/21/2026 at 4:14:11 PM

I wonder whether this is more the fault of Hassabis or Pichai. They are clearly both less capable than Altman or Amodei.

by cubefox

7/21/2026 at 3:52:15 PM

Gemini 3.5 flash is already a pretty good model. But, unfortunately, the primary way you can interact with it for coding is through Antigravity - which is actively developer hostile.

It doesn't matter how good the model is if you're (mostly) forced to use it in Antigravity - which turns any model into crap.

Wake me up when Antigravity doesn't suck.

by onlyrealcuzzo

7/21/2026 at 4:55:23 PM

I use 3.5 flash 10x more than any other model, despite have access to all of them. If I'm going to play a slot machine, I'd rather get the pain over with quickly.

by dakolli

7/21/2026 at 4:31:06 PM

We're almost five years into the whole GenAI thing and we're still relying on these guys to spoonfeed us incremental updates.

It's time for them to start focusing on open-weight models and efficiency. Otherwise there's just a layer of marketing hype and "will it do this?" that has to be cut through for evaluation of each and every release cycle.

Models are getting easier and easier to create. The money, if there's any here, is in the harness the user interfaces with, and the data centers running them.

by lenerdenator

7/21/2026 at 4:12:46 PM

Google seems to be falling way behind the pack. antigravity cli is pure trash. gpt 3.5 pro is now behind and isn't released yet. GPT 6 and Fable 6 releasing next month. What the hell is going on over there ?

by zuzululu

7/21/2026 at 4:20:52 PM

> What the hell is going on over there

Google was late to coding agents and as-per-usual fucked it up with their crazy project management culture.

Usually Google gets away with it due to inertia, however this time they are paying a heavy price because they missed out on the training data that Anthropic and OpenAI have gathered with claude and codex.

by zarzavat

7/21/2026 at 3:57:51 PM

Just switched to AI Plus from Pro, seems like I won't be missing much.

by ece

7/21/2026 at 3:56:58 PM

> we have taken an intentional approach to deploying 3.5 Flash Cyber. The model will be exclusively available to governments and trusted partners

Screw your government! US and Israeli governments should get the least access, but of course we all know they'll be the (only) ones to get full unfiltered access.

by zb3

7/21/2026 at 3:41:48 PM

3.5 Pro must really suck.

by tiahura

7/21/2026 at 3:37:38 PM

They are comparing against their own previous models instead of competitors. Not a great sign.

by holistio

7/21/2026 at 3:33:25 PM

At this point just put the Pareto in the bag bruh

by geooff_

7/21/2026 at 4:17:58 PM

whatever, dude. give gemma5

by accountrequired

7/21/2026 at 4:32:30 PM

is it just me or is this one-upping each other every few days getting ridiculous secreting a whiff of desperation?

by raffael_de

7/21/2026 at 5:02:51 PM

Just you. This is typical market competition in a fast moving field.

by JacobAsmuth

7/21/2026 at 3:49:59 PM

I keep saying this and people dont believe me, but I have b2b saas systems with actual agents running around the clock, and the performance/stability of the flash model is higher than most other models.

Meaning, its predictable with tool calls, wont spin off a million tools/do weird behavior, its reasonable. Even sonnet in a real world decision making scenario is not reliable, or will reason so long its incredibly expensive.

The benchmarks arent catching all the value, and most people have never actually ran an ai agent in a real context that matters

by llmslave

7/21/2026 at 3:58:04 PM

Who's most people? What are you talking about? Most people here use agents every day and I wouldn't trust flash or pro to touch any important project of mine because they're both terrible compared to the competition, waste of time every time I give them a chance

by sureMan6

7/21/2026 at 4:17:52 PM

I mean like an ai agent doing some sort of HR work, not a coding agent. Very few businesses are trusting an autonomous agent.

by llmslave

7/21/2026 at 4:11:58 PM

With all the naysayers on Gemini models I'm curious how many people actually use Gemini regularly?

For me, Gemini models are the most usable. Claude Opus and Mistral always try to turn queries into one-shot enormous commits, which just burns tokens, time and annoys me for something which is still wrong more often than not.

Gemini seems far better at listening to instructions and giving me what I actually want, on top of using far fewer tokens and wasting my time. Fable is the only model that's come close to Gemini Pro for me.

And as this is about Flash, it's exciting, I find Flash can usually get the right answer pretty quickly and without too much nonsense.

by dismalaf

7/21/2026 at 4:03:08 PM

not a google fanboy by any stretch... though i've been thrilled with the flash line of models... i exclusively use it on high, and have found it to be a great fit for increasing productivity 10-fold while maintaining quality... sure it can't just go off and one-shot a bunch of work, but at the complexity level i tend to work at, neither can the frontier in a robust way that i can be confident in... sure i have to be in the loop more, but that helps keep me grounded and course-correct earlier before wasting tokens... and when you sufficiently spec out a coding/software problem, and i mean really document all of the critical nuance, it will successfully satisfy the constraints... the quality is rarely acceptable on first-pass, but it forces me to stay connected to the architecture more than i would be if using a frontier model... i've found this to be a happy middle-ground of productivity and awareness...

by fur-tea-laser

7/21/2026 at 9:02:49 PM

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by DekryptLabs

7/21/2026 at 8:07:44 PM

[dead]

by marshalla

7/21/2026 at 4:27:54 PM

[dead]

by GodelNumbering

7/21/2026 at 4:35:20 PM

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by veloxxn

7/21/2026 at 6:33:51 PM

[dead]

by arjunvrofficial

7/21/2026 at 4:16:54 PM

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by cbossman

7/21/2026 at 4:56:10 PM

[dead]

by CurbStomper

7/21/2026 at 5:34:42 PM

[dead]

by ewaewaewa

7/21/2026 at 3:30:14 PM

tested the models on aistudio. despite that the knowledge cut off is march 2026 it still knows nothing about 2025!

you can check by asking "list notable world events in 2025, only list unplanned" on aistudio. or you can ask for Charlie Kirk, it also does not know. I tried it multiple time to ensure that I didn't not get routed to older models!

> but google has search

irrelevant, without deeper knowledge about cutting edge technologies or latest libraries, all of it suggestions are crap. even you ask it to search it will still use outdated keyword thus only getting outdated information.

in other word, what a disaster!

by npn

7/21/2026 at 3:49:37 PM

Google desperately needs to make some leadership changes within their Gemini team now that they've been surpassed by 3-5 open weight models and risk loosing frontier status all together in the near future.

by kthinckley

7/21/2026 at 3:51:22 PM

Open weight models aren't likely to be open weight in the long-term. China has started considering export controlling and limiting access to model weights [0].

[0] - https://www.ft.com/content/6049a031-9e9b-464c-97bb-414da04d5...

by alephnerd

7/21/2026 at 5:30:17 PM

They don't need to be open weight in the long term; once there's an open-weight Fable-level model with 1M context it'll be pretty much good enough for all coding tasks, no need for new models.

by logicchains

7/21/2026 at 4:52:54 PM

At this point, I think google should consider becoming a hyper scaler for anthropic and open ai, and I predict that that is exactly what they do. The model is no longer the most valuable part of the stack.

by game_the0ry