Xiaomi's MiMo-V2.6-Distill-Qwen-9B is a nine-billion-parameter model trained from Qwen3.5-9B using MiMo-generated examples. The model card describes supervised fine-tuningTaking a trained model and training it a bit more on your own examples so it gets better at one specific job.Full definition →: the smaller model learns from supplied examples of coding and other AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → tasks. Xiaomi positions the released checkpoint as a starting point for further reinforcement-learning research.
The company's evaluation reports improvements over the starting model, but their size varies by task. Its SWE Pro score rises from 32.0 to 44.6, while SWE Verified moves from 60.0 to 61.1. The release therefore provides a concrete model for studying the transfer of agent skills through generated training data, with evidence tied to the reported evaluations.
Terms in this piece · Glossary
fine-tuning — Taking a trained model and training it a bit more on your own examples so it gets better at one specific job.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
distillation — Training a small, cheap model to imitate a big one's outputs, keeping much of the capability at a fraction of the cost.
