alt Hacker NewsI strongly agree with the premise that distillation is not an “attack”.
But that said: K3 is not a distilled version of Fable or Sol. Fable has been barely available and Sol was just released! Moreover, K3 is superior to both models in some domains, according to user scoring on the Arena.
API distillation can’t give you these results anyway. All it is useful for is bootstrapping RL in new domains to get past the “cold start” problem faster. By far, what matters more is the quality and variety of RL environments the model learns from.
API distillation doesn't have to explain all of K3's capabilities for it to have happened. Kimi K3 reproducibly identifies itself as Claude: https://x.com/denisewu/status/2077984660211269870
This behavior is exactly what you'd expect from a model distilled from Claude.
There's a detailed analysis of K3's ambiguous identity here: https://github.com/rgreenblatt/which_claude_is_k3/blob/main/...
This analysis observed K3 identifies itself as Claude approximately 15% of the time.
K3 reproduces Claude's correct current model id, which the real Claude models themselves do not emit. This suggests K3 was trained on Claude data labeled with deployment metadata (API logs, tagged synthetic data), rather than Claude's chat outputs.
And there's an entire Reddit thread discussing Kimi's similarities with Claude https://www.reddit.com/r/LocalLLaMA/comments/1m2w5ge/did_kim...
This analysis shows K3 and Opus/Fable have unexpected correlated outputs https://typebulb.com/u/lab/you-re-relatively-right/full