Xiaomi distills MiMo V2.6 into a 9B model

Xiaomi has published MiMo-V2.6-Distill-Qwen-9B, a nine-billion-parameter model distilled from the company's larger MiMo V2.6 system. The release is aimed squarely at agentic behavior, coding, and tool-use scenarios rather than general chat, and it builds on a Qwen base to reach that footprint.

Distillation is the core idea here: instead of training a small model from scratch, Xiaomi transfers behavior from a stronger teacher model into a more compact student. The payoff is a model that can run on far less demanding hardware while retaining a slice of the capabilities that make bigger systems useful for multi-step tasks.

Why it matters

Much of the practical demand for open models sits in the 7B–13B range, where a single consumer or workstation GPU is enough to serve real workloads. A 9B model tuned for agents and tool calling slots neatly into that gap.

• Sized for accessible hardware in the 7B–13B tier
• Focused on agentic, coding, and tool-use tasks
• Distilled from Xiaomi's MiMo V2.6 rather than trained fresh
• Built on a Qwen base and released on Hugging Face

The model is distributed under a custom license, so teams planning to build on it should check the terms on the model page before deploying. As with any distilled release, the real test will be how much of the parent model's agentic strength survives the shrink.