Xiaomi MiMo-V2.5 is now officially open-sourced！
MIT License, supporting commercial deployment, continued training, and fine-tuning - no additional authorization required.
Two models, both supporting a 1M-token context window :
• MiMo-V2.5-Pro: built for complex agent and coding tasks, ranking No.1 among open-source models on GDPVal-AA and ClawEval
• MiMo-V2.5: a native omni-modal model with strong agent capabilities
A model's value isn't measured by rankings alone — it's measured by the problems it solves.
Let's build with MiMo now!
🤗 Weights: https://t.co/w7wNtXj9Rm
📄 Blog:
SGLang and vLLM support for the MiMo-V2.5 series is here. 🙌
Huge thanks to SGLang project from @lmsysorg and @vllm_project for moving fast and helping developers get started with MiMo-V2.5 on day zero.
MiMo-V2.5 achieved Day-0 adaptation across multiple chip platforms on the first day of open source release.
Huge thanks to our hardware ecosystem partners for helping make MiMo-V2.5 easier to deploy and run efficiently across more environments:
@awscloud、@AMD 、T-HEAD、KUNLUNXIN、Enflame、MetaX、Iluvatar CoreX
From cloud AI chips to domestic accelerators, we’re working with the ecosystem to bring MiMo-V2.5 to more developers and enterprises on day zero.
fine-tuning — Taking a trained model and training it a bit more on your own examples so it gets better at one specific job.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
Why it matters
MIT-licensed weights with day-zero SGLang and vLLM support means these can be self-hosted and fine-tuned without separate licensing, including on non-NVIDIA accelerators.
