I've seen sources like this before. It's all hearsay and promo. I was asking for any publicly available verifiable information regarding the cost of inference at scale. I haven't seen any such info personally which is why I asked.
I'm dying to see S-1 filing for Anthropic or OpenAI. I don't actually think inference is as cheap as people say if you consider the total cost (hardware, energy, capex, etc)
Well they're not public yet so you'll have to put up with rumors. But the numbers are available for companies like DeepSeek say they have an 80% profit margin, so it stands to reason OAI etc would do similar numbers considering they charge much more.
I've seen sources like this before. It's all hearsay and promo. I was asking for any publicly available verifiable information regarding the cost of inference at scale. I haven't seen any such info personally which is why I asked.
I'm dying to see S-1 filing for Anthropic or OpenAI. I don't actually think inference is as cheap as people say if you consider the total cost (hardware, energy, capex, etc)
Well they're not public yet so you'll have to put up with rumors. But the numbers are available for companies like DeepSeek say they have an 80% profit margin, so it stands to reason OAI etc would do similar numbers considering they charge much more.
AFAIK,
1. the 80% margin from 2025 was theoretical,
2. they're relying on distillation/synthetic data for training,
3. and have been very opaque about cross-subsidization of R&D with their models.
The distillation alone adds a big asterisk for comparisons.
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>OpenAI's compute margin, referring to the share of revenue excluding the costs of running its AI models for paying users
Huh?
The reddit summary comment makes no sense. How are they getting revenues without ads or paying customers?
"After" makes more sense.
FTA:
>The company has yet to show a profit and is searching for ways to make money to cover its high computing costs and infrastructure plans.