This is not at all what I would expect because it's trivial to change the training data to replace Claude with Kimi. In fact I'd argue it's almost certainly not saying that due to distillation.
K3 reproduces Claude's internal model identifier when prompted, something which the real Claude models themselves do not emit. This is highly suggestive that K3 was trained on Claude metadata (API logs, tagged synthetic data), rather than Claude's chat outputs.
And it's well documented that Chinese labs are buying large amounts of raw Claude metadata https://www.chinatalk.media/p/how-to-buy-cheap-claude-tokens...
"Caveat: fully AI-generated research."
And that you quoted or paraphrased directly.
Wait what? The reason you wouldn't expect it is because if it was distilled, it would be easy to get rid of self identification? Is that any less true of a non distilled model? I suppose there's lots of ways to interpret it, but the idea that self-identifying as Claude is affirmative evidence that it's not distilled seems to get the weight of the inference exactly backwards.
I wasn't arguing that. I was arguing that even if it was distilled from Claude, the distillation isn't why it identifies as Claude. Therefore identifying as Claude isn't evidence of distillation.
Claude has been caught identifing itself as Deepseek:
https://news.ycombinator.com/item?id=47145081
I don't take that to mean it's necessarily been distilled on Deepseek.
Gemini was supposedly caught identifying as Claude:
https://www.reddit.com/r/ChatGPT/comments/1gslm0t/gemini_mod...
I don't take that to mean it was distilled on Claude.
Claude was caught identifying as ChatGPT:
https://www.reddit.com/r/OpenAI/comments/1e34tkr/why_is_clau...
I don't take that to necessarily mean it was distilled on ChatGPT.
I don’t consider a tweet by Denise Wu, who works at Anthropic, to be reproducible evidence.
I don’t consider “Caveat: fully AI-generated research.” To be someone taking time to analyze anything in great detail.
Because two AI models produce vaguely similar front-end styles when generating similar prompts I also do not consider to be of much value?
I think this is what I mean when I say the U.S. has its head in the sand. The Chinese labs are releasing ~60 page research reports with citations and analyses and evidence and Anthropic is throwing up defensive blog posts with zilch. I’ve seen more detail in a tech blog from Uber than anything I’ve seen from Anthropic.
"Zero evidence" as you claimed earlier isn't accurate. You've moved the goalposts from "evidence" to "raw internal logs I can independently audit," which is a different and very high standard. Sure Anthropic didn't publish logs, IP addresses, timestamps, or account IDs of the accounts involved. But that's true of any cybersecurity breach/abuse disclosure ever made. Companies are furtive to reveal how they detect fraud, because doing so exposes the signals used to detect bad actors, and makes future abuse easier. Not revealing the "evidence" you're asking for is industry standard practice. You're complaining that Anthropic is following industry standard practice, and conveniently defining the "evidence" you need as something Anthropic is never going to publish.
> I don’t consider a tweet by Denise Wu, who works at Anthropic, to be reproducible evidence.
Is the issue here that she works at Anthropic? Because Denise Wu doesn't work there.
> I don’t consider “Caveat: fully AI-generated research” to be someone taking time to analyze anything in great detail.
The experiments were run by Ryan Greenblatt, who is a real AI safety researcher (at Redwood Research).
The identity experiments and Greenblatt analysis are trivially reproducible. The methodology, code, and metrics are all there in the Github repository. You can ask your preferred AI to independently replicate these results, and it will give you a result within an hour.
You’ve also reduced the evidence to “two models producing vaguely similar front-end styles,” which is not what either analysis shows.
From the analysis, Kimi K3 identifies itself as Claude 15% of the time. How do you explain that? Qwen and GPT identify themselves as Claude 0% of the time.
If a long document is too much analysis for you, someone else made a simple chart which measures the KL divergence between Kimi K3 and other major models. They found K3 is unusually similar to Fable 5 & Opus models. That is, Kimi K3 has an very similar style and phrasing to that of Anthropic models. That behavior is expected from a model distilled from Claude.
Qwen and GPT have special guards that trigger when asked to identify, Kimi doesnt. I dont understand the argument. Kimi is an LLM and does not know what it is. It will give you the most likely answer which sometimes is Claude.