alt.hn

4/6/2026 at 9:52:08 PM

Anthropic expands partnership with Google and Broadcom for next-gen compute

 https://www.anthropic.com/news/google-broadcom-partnership-compute

by l1n

4/7/2026 at 12:17:10 AM

I guess gigawatts is how we roughly measure computing capacity at the datacenter scale? Also saw something similar here:

> Costs and pricing are expressed per “token”, but the published data immediately seems to admit that this is a bad choice of unit because it costs a lot more to output a token than input one. It seems to me that the actual marginal quantity being produced and consumed is “processing power”, which is apparently measured in gigawatt hours these days. In any case, I think more than anything this vindicates my original decision not to get too precise. [...]

https://backofmind.substack.com/p/new-new-rules-for-the-new-...

Is it priced that way, though? I assume next-gen TPU's will be more efficient?

by skybrian

4/7/2026 at 12:50:55 AM

> but the published data immediately seems to admit that this is a bad choice of unit because it costs a lot more to output a token than input one

And, that's silly, because API pricing is more expensive for output than input tokens, 5x so for Anthropic [1], and 6x so for OpenAI!

[1] https://platform.claude.com/docs/en/about-claude/pricing

[2] https://openai.com/api/pricing

by nomel

4/7/2026 at 2:40:39 AM

I think for the same model wall time is probably a more intuitive metric; at the end of the day what you’re doing is renting GPU time slices.

Large outputs dominate compute time so are more expensive.

IMO input and output token counts are actually still a bad metric since they linearise non linear cost increases and I suspect we’ll see another change in the future where they bucket by context length. XL output contexts may be 20x more expensive instead of 10x.

by AlphaSite

4/8/2026 at 6:03:28 PM

> I think for the same model wall time is probably a more intuitive metric; at the end of the day what you’re doing is renting GPU time slices

This is a bit too much of a simplification.

The LLM provider batches multiple customer requests into one GPU/TPU pass over the weights, with minimal latency increase.

The LLM provider may in fact be renting GPUs by the second, but the end user isn't. We the end users are essentially timesharing a pool of GPUs without any dedicated "1 vGPU" style resource allocation. In such a setting, charging by "GPU tick" sounds valid, and the various categories of token costs are an approximation of cost+margin.

by yencabulator

4/7/2026 at 6:56:09 PM

As a customer, it's nice that I can quantize and count the units of cost in an understandable way.

For Anthropic, as a business bleeding money, it's probably nice to have value-based pricing, for the tokens, so innovation (like computation efficiency improvements) can result in some extra margin. If they exposed the more direct computation cost, they could never financially benefit from any improved efficiency, including faster hardware!

by nomel

4/7/2026 at 3:39:48 AM

They already bucket when context goes above 200k

by nsomaru

4/7/2026 at 4:55:21 AM

No longer

by refulgentis

4/7/2026 at 12:34:13 AM

Gigawatts seems like more a statement of the power supply and dissipation of the actual facility.

I’m assuming you can cram more chips in there if you have more efficient chips to make use of spare capacity?

Trying to measure the actual compute is a moving target since you’d be upgrading things over time, whereas the power aspects are probably more fixed by fire code, building size, and utilities.

by brokencode

4/7/2026 at 1:18:00 AM

Measuring data centers in watts is like measuring cars in horsepower. Power isn't a direct measure of performance, but of the primary constraint on performance. When in doubt choose the thermodynamic perspective.

by delichon

4/7/2026 at 7:08:20 AM

Gigawatts are units of power, gigawatthours are units of energy.

The equivalent of cars would be pricing by how much gas you burned, not horsepower.

by pepperoni_pizza

4/7/2026 at 11:35:55 AM

1 horsepower = 745.7 watts

by delichon

4/7/2026 at 2:14:56 AM

I mean a single nuclear reactor delivers around 1GW, so if a single datacenter consumes multiple of those, it gives a reasonably accurate idea of the scale.

by stingraycharles

4/7/2026 at 6:05:53 PM

This conversation is confusing because OP didn't use the same units as the person in the quote.

by franktankbank

4/7/2026 at 9:39:26 AM

It's not really a stable measure of compute, but it's a good indication of burn rate as energy cost is something we closely track in economies and it actually dominates a lot of the cost of operating data centers. At least short term. Over time we'll get more tokens per energy unit and less dollars for the hardware needed per energy unit. Tokens currently is too abstract for a lot of people. They have no concept of the relation ship of numbers of tokens per time unit and cost. Long term there's going to be a big shift from op-ex to cap-ex for energy usage as we shift from burning methane and coal to using renewables with storage.

by jillesvangurp

4/7/2026 at 10:30:59 AM

We need a Moore's law for tokens, and energy.

by amelius

4/7/2026 at 1:07:10 AM

That these data centers can turn electricity + a little bit of fairly simple software directly into consumer and business value is pretty much the whole story.

Compare what you need to add to AWS EC2 to get the same result, above and beyond the electricity.

by twoodfin

4/7/2026 at 1:23:08 AM

That's a convenient story, but most consumers' and businesses' use of AI is light enough that they could easily run local models on their existing silicon. Resorting to proprietary AI running in the datacenter would only add a tiny fraction of incremental value over that, and at a significant cost.

by zozbot234

4/7/2026 at 1:57:14 AM

Sure but where the puck is going is long-running reasoning agents where local models are (for the moment) significantly constrained relative to a Claude Opus 4.6.

by twoodfin

4/7/2026 at 2:20:21 AM

I'm looking forward to running a Gemma 4 turboquant on my 24GB GPU. The perf looks impressive for how compact it is.

I often get a 10x more cost effective run processing on my local hardware.

Still reaching for frontier models for coding, but find the hosted models on open router good enough for simple work.

Feels like we are jumping to warp on flops. My cores are throttled and the fiber is lit.

by astral_drama

4/7/2026 at 1:11:47 AM

$19B -> $30B annualized revenue in a month?

Feels like the lede is buried here!

by ketzo

4/7/2026 at 2:49:36 AM

All of big tech (except Google obviously) is pushing hard for Claude Code internally. I’m talking “you all have unlimited tokens and we’re going to have a leaderboard of who used the most” kind of push.

by strongpigeon

4/7/2026 at 4:02:45 AM

"we’re going to have a leaderboard of who used the most"

Yeah I've seen stuff like that and it's a bit bewildering for me. Feels a bit like AWS is new and we're competing to see who can deploy the most EC2 instances.

by causal

4/7/2026 at 6:16:32 AM

It’s the crudeness of available management methods at play. Quite exposing for the profession, really (remember lines of code as measure of productivity?).

by kubb

4/7/2026 at 1:42:13 AM

Also, very very recently they said in a court filing that their lifetime revenue was "at least" 5 billion. Which is it?

by 9cb14c1ec0

4/7/2026 at 1:58:59 AM

Their disclosed run rate was 14bn around the time of those filings IIRC, they started showing meaningful revenue around start of 2025, so if you just linearly extrapolate up that would give you ~7bn-ish actual revenue over that period. The more the growth is weighted towards the last few months the more that number goes down

So I don't think those numbers are really in tension at all

by dauhak

4/7/2026 at 1:55:52 AM

If your revenue doubles every month, then in the first month where you make $2.5B, your total lifetime revenue has been $5B ($2.5B this month, $1.25B the month before, etc. is a simple geometric series). But your current revenue run rate for the next year will be $2.5B x 12 = $30B.

They're not quite growing that fast, but there's nothing inherently inconsistent between these claims... as long as the growth curve is crazy.

by tabbott

4/7/2026 at 2:09:30 AM

The reality is

1) It's in their interest to distort numbers and frame things that make them look good - e.g. using 'run-rate' 2) The numbers are not audited and we have no idea re. the manner in which they are recognising revenue - this can affect the true compounding rate of growth in revenues

by kdkl

4/7/2026 at 2:33:25 AM

The numbers are certainly audited by their investors. Anthropic isn't foreign to PR talk, but investors know what to look for in their book. They aren't stupid unlike how they are viewed on HN.

There are more investment money than Anthropic need. They can pick and choose.

by signatoremo

4/7/2026 at 2:34:18 AM

"The numbers are certainly audited by their investors."

Hahaha.

Mate nobody cares about that nor trusts it. Everyone is waiting in anticipation for the S-1 filing.

by kdkl

4/7/2026 at 4:20:10 AM

I do, and I do trust the numbers. I doubt Anthropic is pursuing fraud given that they already don't have enough compute to serve demand. What is the point of lying to the public, investors and risk going to jail?

by aurareturn

4/7/2026 at 9:26:59 AM

Money? Bankman-Fried wasn't the only one.

by IsTom

4/7/2026 at 1:50:20 AM

Curious - what’s this court filing?

by xtacy

4/7/2026 at 1:55:52 AM

Too lazy to pull up a url, but it was a filing by Anthropic's CFO in the Anthropic v Department of War case.

by 9cb14c1ec0

4/7/2026 at 1:49:51 AM

Doesn't that beat openai in revenue?

by oidar

4/7/2026 at 1:17:03 AM

[flagged]

by ai-x

4/7/2026 at 1:32:42 AM

I think you can argue that AI is going to explode and take over the economy, and it’s still a bubble.

I think one possible route is that cloud capacity just becomes totally commoditized and none of the hyperscalers will be able to extract the kinds of profit margins that would allow them to make a good return on their investment (model makers will fall victim to this too). Ultimately, what may happen is that market competition for everything explodes since AI and robots can do all the work, prices for everything (goods, services, assets) collapses, and no one is really any richer than anyone else.

by baron816

4/7/2026 at 1:38:30 AM

Even if the AI frontier becomes "totally commoditized" it will still be reliant on a scarce factor, namely leading-edge chips. Chipmakers will ultimately capture that value, because competing it away would require expanding the industry and that's a very slow process involving billion-dollar expenses planned far in advance (multiple years, and that lead time can only expand further as the required scale gets even larger).

by zozbot234

4/7/2026 at 2:51:45 AM

You don’t think open AI models will eventually be able to design and build chips and fabs and all their components?

by baron816

4/7/2026 at 1:48:32 AM

Except you're neglecting the fact that LLMs can become more efficient.

The magical thing about software is that efficiency gains can come pretty quickly relative to other industries.

by kdkl

4/7/2026 at 2:36:44 AM

We're already seeing this with Qwen 3.5 and Gemma 4. They're better than GPT-3.5 and they run on smartphones and old laptops.

by MarsIronPI

4/7/2026 at 5:45:43 AM

AI being a bubble it's not mutually exclusive of being a real and useful technology and the existence of non-snake oil companies.

Cisco was a bubble in the dot com crash, despite being a company that provide real value and profit, just not at the level of the crazy expectations from the time.

by javchz

4/7/2026 at 6:38:35 AM

I'm literally talking about the fact that Anthropic is making $30B Annual Revenue, which is the result of less than $10B investment two years ago.

The public hasn't seen the insane ROA/ROI on GPUs. So all AI adjacent stocks are massively undervalued.

by ai-x

4/7/2026 at 7:34:00 AM

I’m not sure your numbers are accurate, they raised $13bn in funding in September last year. Also do note that a lot of the money is cross-subsidized by Google who is funding the TPUs as an investment, so I wouldn’t be so confident that they are returning money quite yet (though it does seem that Anthropic might make it).

by bootsmann

4/7/2026 at 1:31:05 AM

[flagged]

by mrcwinn

4/7/2026 at 1:53:33 AM

[flagged]

by kdkl

4/7/2026 at 2:14:02 AM

Interesting to see Anthropic investing in compute infrastructure. The bottleneck I keep hitting is not raw compute but where that compute lives — EU customers increasingly need guarantees their data stays in-region. More sovereign compute options in Europe would unlock a lot of enterprise AI adoption.

by mahadillah-ai

4/7/2026 at 2:22:47 AM

[flagged]

by semiinfinitely

4/7/2026 at 9:39:33 AM

[dead]

by 243341286

4/7/2026 at 12:41:31 AM

I’m surprised Anthropic wanted to partner with Broadcom when they have such a negative reputation with antics such as their VMWare acquisition.

by cebert

4/7/2026 at 12:46:48 AM

I think it’s also important to add the context that Broadcom’s CEO, Hock Tan, went on CNBC in October and had a vacuous conversation with Jim Cramer about their OpenAI “deal” at the time [0]. Nothing of substance was said, it was just endless loops about the opportunity of AI. It is now 6 months later and there has been nary a peep from Broadcom about any updates.

I think Anthropic is a more grounded company than OpenAI because Sam Altman is insane, but it is still playing the same game.

[0] https://www.youtube.com/watch?v=pU2HhJ3jCts

by Eufrat

4/7/2026 at 12:59:51 AM

Broadcom builds the TPU chip. Google designs it. You can’t avoid partnering with Broadcom if you want TPUs in significant volume .

by thundergolfer

4/7/2026 at 7:46:47 AM

TSMC builds the TPU chip. Broadcom does the rest of the electronics (motherboard, networking, etc...)

by Jyaif

4/7/2026 at 7:53:09 AM

And and Broadcom designs a huge part of the chip. They take Google's (mostly) logical design and providing everything TSMC need to physically make the chip (including imports g IP such as serdes, PLLs, and test).

by nsteel

4/7/2026 at 1:02:12 AM

The VMware s/w rental market has no relevance to this deal, any more than the IBM role in data processing in germany in the 1930s had any relevance to their business in Israel in the 60s, or Oracle's failure in the DC market impacts licencing of the database product.

It's just not material. Broadcom make devices they need, and Broadcom want to sell those devices and exclude another VLSI company from selling, so the two have an interest in doing business. That's all there is to it.

About the most you could say is that the lawyers drafting whatever agreement they sign to, will reflect on the contract in regard to future changes of pricing and supply, in the light of what Broadcom did with VMWare licencing costs.

by ggm

4/7/2026 at 12:55:01 AM

Broadcom makes the TPU. If you want TPUs, you are working with Broadcom whether you want to or not.

by jeffbee

4/7/2026 at 9:03:07 AM

On a tangential note: It seems the whole theater with the DoD is over for now, am I seeing this right?

by chimpanzee2