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Frontier Models

Model distillation techniques, efficiency, and prevention

Distillation token requirements (50-100B sufficient), logit access restrictions, and resilience mechanisms

6 posts · First seen 2026-02-23 · Last activity 2026-02-23

Time	Author	Post
2026-02-23T21:18	@yacinelearning	even more bullish on @MiniMax_AI wild stuff to switch distillation mid-flight like that damn ↩ reply parent
2026-02-23T20:33	@opentensor	RT @const_reborn: Distillation is proof that intelligence is a commodity — it can be extracted, distilled, transferred and hoarded by labs.
2026-02-23T19:53	@WolframRvnwlf	@Teknium "Distillation attacks" - that's a new one. If that's considered an attack, then we really need to ask what LLMs themselves are under that framing. 🤔 ↩ reply parent
2026-02-23T19:36	@tphuang	I really wonder who the sources are since 3.1 & 3.2 were released w/o these leaks & we've heard v4 rumors for like a month. As for Chinese labs distilling Claude, I do wonder how many of those prompts are for benchmarking vs using result to build new models. After all, if it is so easy to build your own models by prompting Claude for training data, why aren't more firms out there able to distill leading models from Opus? As usual, take these rumors w/ caveat. When DeepSeek is ready to release V4, it will be released.
2026-02-23T19:18	@sytelus	16M exchanges is surprisingly small to distill frontier model. Also, this is across at least 3 models. So just 50-100B tokens is all you need to approximate target frontier model! https://t.co/sDubwjOFgL
2026-02-23T19:00	@EitanTurok	these companies only have access to the final sampled tokens, not the raw logits. This makes it harder to distill. very surprising that DeepSeek has only 150k exchanges while moonshot has 3.4M and minimax has 13M exchanges. Does Deepseek not need to distill? Any research on preventing distillation when you have access to a model's text?

@yacinelearning 2026-02-23T21:18

even more bullish on @MiniMax_AI wild stuff to switch distillation mid-flight like that damn

↩ reply parent

@opentensor 2026-02-23T20:33

RT @const_reborn: Distillation is proof that intelligence is a commodity — it can be extracted, distilled, transferred and hoarded by labs.

@WolframRvnwlf 2026-02-23T19:53

@Teknium "Distillation attacks" - that's a new one. If that's considered an attack, then we really need to ask what LLMs themselves are under that framing. 🤔

↩ reply parent

@tphuang 2026-02-23T19:36

I really wonder who the sources are since 3.1 & 3.2 were released w/o these leaks & we've heard v4 rumors for like a month. As for Chinese labs distilling Claude, I do wonder how many of those prompts are for benchmarking vs using result to build new models. After all, if it is so easy to build your own models by prompting Claude for training data, why aren't more firms out there able to distill...

@sytelus 2026-02-23T19:18

16M exchanges is surprisingly small to distill frontier model. Also, this is across at least 3 models. So just 50-100B tokens is all you need to approximate target frontier model! https://t.co/sDubwjOFgL

@EitanTurok 2026-02-23T19:00

these companies only have access to the final sampled tokens, not the raw logits. This makes it harder to distill. very surprising that DeepSeek has only 150k exchanges while moonshot has 3.4M and minimax has 13M exchanges. Does Deepseek not need to distill? Any research on preventing distillation when you have access to a model's text?

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Model distillation techniques, efficiency, and prevention

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