4 ms·
Rumors say chatgpt/claude/gemini/etc are in the 100s of teras. True?
by sylware 2mo ago
Rumors say chatgpt/claude/gemini/etc are in the 100s of teras. True?
- wren6991 2mo agoI'll ask my uncle (he works for Nintendo) and get back to you on that one
- sylware 2mo agoMy question is that wrong?
- wren6991 2mo agoSorry if the joke didn't land; I have heard a lot of different numbers for the size of US labs' models, but never seen any of them substantiated, so I think you're likely to just get more rumours in answer to this question. My personal take, with no sources: 100T sounds excessively high given they need to be able to actually serve these things on commercially available hardware. I would guess they are in the same order of magnitude as the Chinese frontier models. It's possible their edge is in RL training methods, training-time compute, and access to data (e.g. from customers' CC/Codex sessions), not in model size.
- sylware 2mo agoAllright! Well, the rumors I got are around 100T for those frontier models: reading stuff here and there on internet, on discussion forums with guys pretending running AI models, etc. This is so hard to sort the true from the false nowadays. If LLM becomes that good at coding, I'll have to run an open weight one locally.
- wmf 2mo agoNo, rumors say 5-10T.
- sylware 2mo agoYour rumors have one less 0 than my rumors. :) I have no clue anyway.
- happosai 2mo agoMaybe you could estimate frontier model sizes from AWS bedrock pricing?
- sylware 2mo agoHow???
- happosai 2mo agoBecause bedrock isn't subsided by anyone. Or at it would be financially insane go do so. 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.