Xiaomi's MiMo-V2.6 RL Run: What Actually Goes Into the Checkpoint
tokenbender · x · 2026-09-21
A technical write-up on Xiaomi's MiMo-V2.6 reinforcement learning run, focused on the question of what actually goes into the checkpoint.
The piece frames its background around how, for most of the past 3-4 years, the public story of a frontier model has been packaged around a familiar set of disclosures, starting with parameter count (a detail even frontier labs now...). From there the author examines what a model checkpoint actually contains in an RL training pipeline and how that affects reproducibility and subsequent iteration.
(The post is a retweet with truncated body text; only the topic of Xiaomi's MiMo-V2.6 RL training and checkpoint composition can be confirmed.)
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