Earlier quoted context omitted.
There's no evidence they're making money, and we already know from the projected datacenter capacity in a few years that there will be for more supply than demand, so the major providers will have to repay that debt. Even if they are making money on inference, it's nowhere near enough to cover the bill. It's a losing proposition either way, especially with Chinese models now in play.
There is. Specifically the pricing for open models from third party providers on OpenRouter since inference is a "commodity" at this point. Unless we think that Opus/GPT-5.6 are many times less efficient than GLM 5.2 or Kimi Openai and Anthropic are making money from inference. > it's nowhere near enough to cover the bill Obviously it does not cover R&D, marketing and other spending but nobody has ever claimed that h…
DeepSeek V4 Flash on a Single AMD MI300X
111–114 of 114 posts
Re: DeepSeek V4 Flash on a Single AMD MI300X
#112Is their hardware programming interface reasonable for implementing inference of frontier models: no quantization, several tera params? BTW, how many many params open weight frontier models have? A few teras, 100s of teras?
Kimi-K3: 2.8T Qwen3.8-Max: 2.4T DeepSeek V4 Pro: 1.6T DeepSeek V4 Flash: 284B (all are total parameter counts, not active parameters)
Re: DeepSeek V4 Flash on a Single AMD MI300X
#113Earlier quoted context omitted.
Did you read your own article? It's well less than $3 trillion. Now let's build the model out more. What is the projected revenue, backlog, improvements in existing big tech businesses such as AI helping Meta's ad business?
Did you read beyond the headline? It's 1.65 trillion hidden and 1.35 trillion overt - which sums up to 3 trillion.
Can you now analyze backlog? For example, Microsoft and Amazon have backlogs of $1.45 trillion. Not including Google, Oracle, Meta.
Re: DeepSeek V4 Flash on a Single AMD MI300X
#114Earlier quoted context omitted.
Maybe you could estimate frontier model sizes from AWS bedrock pricing?
How???
Compare the of bedrock inference on known open source models to bedrock pricing of SOTA models. If the price of SOTA model is 10x qwen3 480B the the SOTA models is max 10x larger. Obviously anthropic Openai etc take a hefty cut from AWS for letting or run their models, so 10x more expensive model is probably only 5x heavy to run.