Open source Xiaomi MiMo-V2.5 and V2.5-Pro are among the most efficient (and affordable) at agentic 'claw' tasks

Xiaomi, the Chinese firm best known for its smartphones and electric vehicles, has lately been shipping some incredibly affordable and high-powered open source AI large language models.

The trend continued today with the release of Xiaomi MiMo-V2.5 and Xiaomi MiMo-V2.5-Pro, both available under the permissive, enterprise-friendly MIT License, making them suitable for use in production in commercial applications. Enterprises and individual/independent developers can now download either of the models (and more Xiaomi open source options) directly from Hugging Face, modify them as needed, and run them locally or on virtual private clouds as they see fit.

The most notable attribute of these models besides the open source licensing is that, according to Xiaomi's published benchmarks, they are among the most efficient available for agentic "claw" tasks, that is, powering systems such as OpenClaw, NanoClaw and Hermes Agent, in which users can communicate with them directly over third-party messaging apps and have the agents go off and complete tasks on the human user's behalf, such as making and publishing marketing content, running accounts, organizing email and scheduling, etc.

As Xiaomi's ClawEval benchmark chart shows, both MiMo-V2.5 and the Pro version in particular appear near the top left of the chart, indicating high performance in completing the benchmarked claw tasks while using the fewest amount of tokens — saving the human user money, especially in a world where more and more services such as Microsoft's GitHub Copilot are moving to usage-based billing.

In fact, the Pro model leads the open-source field with a 63.8% success rate, consuming only ~70K tokens per trajectory. This is roughly 40–60% fewer tokens than those required by Anthropic Claude Opus 4.6, Google Gemini 3.1 Pro, and OpenAI GPT-5.4 to achieve comparable results.

By combining a massive 310B-parameter architecture with a highly efficient "active" footprint and a native 1-million-token context window, Xiaomi MiMo is challenging the dominance of closed-source frontier models from Google and OpenAI, especially when it comes to the latest and greatest craze in enterprise AI deployments — agentic tasks and "claws" similar to OpenClaw.

Xiaomi has released two distinct versions of the model: MiMo-V2.5 (the "Omni" multimodal specialist) and MiMo-V2.5-Pro (the "Agent" specialist). While the base model provides native multimodality, the MiMo-V2.5-Pro is specifically engineered for "long-horizon coherence" and complex software engineering.

On the GDPVal-AA (Elo) benchmark, the Pro model achieved a score of 1581, surpassing competitors like Kimi K2.6 and GLM 5.1. Xiaomi researchers further released data on several high-complexity tasks performed autonomously by V2.5-Pro, including implementing a complete SysY Compiler in Rust in 4.3 hours and building a full-featured video editor in 11.5 hours.

At the heart of MiMo-V2.5 is a Sparse Mixture-of-Experts (MoE) architecture. While the model boasts a total of 310 billion parameters, only 15 billion are "active" during any given inference cycle. Meanwhile, V2.5-Pro is a 1.02 trillion-parameter Mixture-of-Experts model with 42 billion active parameters.