MiMo-V2.6: Scaling Reinforcement Learning from Scratch
Building Xiaomi's MiMo-V2.6 RL recipe from the ground up — the importance-sampled GRPO objective, group-relative advantages and dynamic sampling, hack zeroing, Groupwise Reward Synthesis, Groupwise Advantage Redistribution, the group-relative length penalty, mass-conserving segment penalties, top-p candidate replay, router freezing, and the Little's-law Sample Mixer — all derived step by step on one four-rollout coding group.