# MiMo-V2.6

After the MiMo-V2.6 release, repeated identical tool calls in agentic settings were traced to a reward blind spot in reinforcement learning: correctness was rewarded, but excessive calling below the penalty threshold was not. The team first trained a single-turn RL teacher that learned when to stop, then merged that behavior into the main model through multi-teacher on-policy distillation. Repetition rates for MiMo-V2.6-Pro and MiMo-V2.6-Flash fell substantially across context lengths and agent harnesses, and the full training run cost about $90,000, 4% of the estimated $2.31 million for restarting the MixRL alternative.

After the MiMo-V2.6 release, repeated identical tool calls in agentic settings were traced to a reward blind spot in reinforcement learning: correctness was rewarded, but excessive calling below the penalty threshold was not. The team first trained a single-turn RL teacher that learned when to stop, then merged that behavior into the main model through multi-teacher on-policy distillation. Repetition rates for MiMo-V2.6-Pro and MiMo-V2.6-Flash fell substantially across context lengths and agent harnesses, and the full training run cost about $90,000, 4% of the estimated $2.31 million for restarting the MixRL alternative.