MiMo-V2.5-Pro is Xiaomi's flagship open-weights language model, built as a Mixture-of-Experts architecture that pairs roughly one trillion total parameters with around 42 billion active per token. That deliberate sparsity keeps inference lean while still letting the model reach scores that put it at the top of open-weights rankings, including a tied first-place finish on the Artificial Analysis Intelligence Index and a strong showing on SWE-bench Pro. A one-million-token context window backs the design intent: long, stateful agent sessions where the model must plan, call tools repeatedly, and keep coherent reasoning across many steps. Xiaomi positions it as a generalist workhorse for coding agents and other high-intensity agentic workloads, explicitly benchmarking its autonomy against top-tier proprietary systems.</item>
The V2.5 release marks Xiaomi consolidating its lineup into a single smarter, cheaper tier, with the Pro variant aimed at developers who want frontier-class reasoning without frontier-class token bills. In launch reporting it is described as capable of 1,000 plus autonomous tool calls per session and matching Claude Opus 4.6 on demanding agent tasks, while running at a fraction of the per-token cost. Real-world deployment fits naturally around long-running coding agents, multi-step research assistants, and any workflow that benefits from an ultra-long context and aggressive caching economics. With the previous V2 series already deprecated in favor of V2.5, the model is clearly intended as Xiaomi's forward-looking default, and an UltraSpeed variant hints at a near-term path toward much higher tokens-per-second serving for latency-sensitive agent loops.</item>
