[refulgentis]

I didn’t participate in the discussion yesterday because I find it implausible Fable was available long enough (3-4 weeks cumulative?) to get data and train and have it fundamentally affect.

But I don’t grok training enough to know that’s silly.

If my new prior is you can…that’s a pretty thin moat that’s essentially indefensible.

[credit_guy]

My guess is they used the other Anthropic models extensively for synthetic data generation. The top most similar models for K3 are (lower means more similar)

Fable 5 -> 0.42

Opus 4.8 -> 0.45

Sonnet 5 -> 0.45

Opus 4.7 -> 0.46

Grok 4.3 -> 0.52

There's an obvious jump at Grok 4.3, and it would not surprise me that the similarity there is because Grok used Anthropic models for training too (you can get the similarity list for Grok and it does look like the top most similar models for Grok are either Anthropic models or some Chinese models).

The damning evidence that K3 used Anthropic models for training is that K3 is more similar to those models than it is to K2.6. If you look at the Anthropic, OpenAI or Google models, they are most similar with their own other models. Not so with K3, where K2.6 is less similar than 15 other models.

Now, why is Fable 5 the most similar to K3 and not Opus 4.8. I think it's quite likely that K3 did some fine tuning at the end, when Fable 5 became available. They probably had all the infrastructure in place, and Mythos had been announced for months, so they were probably waiting for the second the newest Anthropic model was released to start using it for synthetic data generation.

[throwa356262]

Note that until last generation all Chinese models were relatively small. This was mainly due to lack of training hardware, but as soon as the new Huawei NPUs started shipping some Chinese labs switched to larger models:

Deepseek: 670B to 1.6T

Moonshot: 1.1T to 2.8T

Xiaomi: 310B to 1T

The new models also use a different architecture so I would assume in tests they will look different from previous generations.

Z.ai (GLM) and MiniMax on the other hand have continued training existing models (with some surgical changes to improve long context memory) so they should score similarly in these tests.