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sergiopaniego 
posted an update 2 days ago
Post
7279
Frontier models use distillation as a step of their post-training pipelines.

In 2026 it has three jobs: compress a big model into a small one, merge RL experts into a single model, and let a model teach itself.

I wrote up which frontier models use each one and how: https://huggingface.co/blog/sergiopaniego/distillation-2026

It pairs with Class 2 of the Training an Agent series Ben and I are doing, where we teach these techniques hands-on with TRL!

very helpful blog, thank you 🤗

The self-teaching job is the one that doesn't compress cleanly. On long-horizon agent trajectories the KL signal piles onto shallow tokens and leaves the deep decision turns under-trained. Does Class 2 weight supervision per-turn, or stay trajectory-level?

Thanks for sharing!