Xiaomi released MiMo-V2.5-Pro, an open-weight AI model that rivals Anthropic's Claude Opus 4.6 on coding tasks while consuming 40 to 60 percent fewer tokens. The model performs nearly identically to Claude on benchmarks but operates far more efficiently.
The release reflects a shift in how Chinese AI developers compete. Rather than chasing higher benchmark scores, companies like Xiaomi and Deepseek now focus on operational efficiency and autonomous task duration. Lower token consumption means cheaper inference costs and longer model runtime on single tasks without additional resources.
MiMo-V2.5-Pro targets developers who need extended autonomous coding sessions. The efficiency gains matter for production environments where token costs directly impact margins. By matching Claude's coding performance at a fraction of the computational expense, Xiaomi positions the model as a practical alternative for enterprises juggling budget constraints.
This move underscores how the open-weight model space has matured. Competition no longer centers on raw capability alone. Providers now optimize for real-world deployment scenarios where efficiency, cost per inference, and sustained performance determine adoption rates.