Comment by dvt
1 month ago
I don't want to respond to 100 comments about the same thing, and this one happens to be on top, so, in my humble opinion:
(1): You don't have to be an Ed Zitron disciple to infer that OpenAI and Anthropic are likely overvalued and that Nvidia is selling everyone shovels in a gold rush. AI is a game-changing technology, but a shitty chat interface does not a company make. OpenAI and Anthropic need to recoup astronomical costs used in training these models. Models that are now being distilled[1] and are quickly becoming commoditized. (And frankly, models that were trained by torrenting copyrighted data[2], anyway.) Many have been calling this out for years: the model cannot be your product. And to be clear, OpenAI/Anthropic most definitely know this: that's why they've been aquihiring like crazy, trying to find that one team that will make the thing.
(2): Token prices are significantly subsidized and anyone that does any serious work with AI can tell you this. Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like. The end-state here is likely some models running locally and some running in the cloud. But the current state of OpenClaw token-vomit on top of Claude is fiscally untenable (in fact, this is why Anthropic shut it down).
(3): This is typical Dropbox HN snark[3], of which I am also often guilty of. I really don't think AI coding is a killer product and this seems very myopic—engineers are an extreme minority. Imo, the closest we've seen to something revolutionary is OpenClaw, but it's janky, hard to set up, full of vulnerabilities, and you need to buy a separate computer. But there's certainly a spark there. (And that's personally the vertical I'm focusing on.)
> Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like.
Qwen3.5-122B-A10B is $0.26 input, $2.08 output. Where's the subsidy? It's ten times cheaper than Opus. Or did you mean that we're subsidizing their training? But then "OpenClaw token-vomit on top of Claude is fiscally untenable" makes no sense.
Yeah, I don't know where you got your costs from. Bare metal providers are significantly cheaper than Anthropic.
Maybe he's comparing the renting price of a bare metal server on its own, and doesn't realise how drastically cheaper they are to batch together for an API provider.
> And to be clear, OpenAI/Anthropic most definitely know this: that's why they've been aquihiring like crazy, trying to find that one team that will make the thing.
Anthropic is up to $30B annual recurring revenue. I wish I had failing business models like that.
> Token prices are significantly subsidized and anyone that does any serious work with AI can tell you this. Go use an almost-SOTA model (a big Deepseek or Qwen model) offered by many bare-metal providers and you'll see what "true" token prices should look like.
I'm not sure what think you are saying here, but if you look at the providers for both "almost-SOTA model (a big Deepseek or Qwen model)" or at the price for Claude on AWS Bedrock, Azure or on GCP you will quickly see inference is very profitable.
> Anthropic is up to $30B annual recurring revenue. I wish I had failing business models like that.
And profit? A company can have $300B annual revenue, and still be a failing business if it's making a loss.
Somewhere along the line we seem to have forgotten this basic fact. Eventually there will be no more rounds of funding to feed the fire.
Anthropic has raised $64B in total since they were founded.
Even if you say we are going to measure profit in the very special hacker news way of looking at money taken in from customer revenue against money invested and we say they can't do things like counting building data centers or buying GPUs as capital expenses and instead have to count them against profit then in 2 years time they will have made more money than they have taken in investment.
That is extraordinary.
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Costs can always be optimized, revenue is much harder to optimize.
It is easy to get 30B when you resell something you buy for 50B
The proverbial "50B" is investment in next year's model. The current model cost under "30B", and therefore "is profitable". It is a bet on scaling, yes, but that's been common throughout the industry (see, eg, Amazon not being profitable for many years but building infrastructure)
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