Agree, but I guess the Opus 4.6 is 10x larger, rather than Chinese models being 10x more efficient. It is said that GPT-4 is already a 1.6T model, and Llama 4 behemoth is also much bigger than Chinese open-weight models. Chinese tech companies are short of frontier GPUs, but they did a lot of innovations on inference efficiency (Deepseek CEO Liang himself shows up in the author list of the related published papers).
I agree that Opus almost definitely isn't anywhere near that big, but AWS throughput might not be a great way to measure model size.
According to OpenRouter, AWS serves the latest Opus and Sonnet at roughly the same speed. It's likely that they simply allocate hardware differently per model.
My understanding is that for MoE with top K architecture, model size doesn't really matter, as you can have 10 32GB experts or a thousand, if only 2-3 of them are active at the same time, your inference workload will be identical, only your hard drive traffic will incread.
Which seems to be the case, seeing how hungry the industry lately has been for hard drives.
GPT-4 was likely much larger than any of the SOTA models we have today, at least in terms of active parameters. Sparse models are the new standard, and the price drop that came with Opus 4.5 made it fairly obvious that Anthropic are not an exception.
wasn't GPT 4 the model that was so expensive for open AI to run that they basically completely retired it in favor of later models which became much stronger but weren't as expensive for them to run?
