Xiaomi released and open-sourced the MiMo-V2.6 series of natively omnimodal generative AI models, including MiMo-V2.6-Pro and a Flash variant. MiMo-V2.6-Pro supports a 1-million-token context window and the Pro-UltraSpeed variant delivers up to 20 times faster output than Pro at the same quality. The update changes availability and deployment by offering the models via Xiaomi’s AI Studio, MiMo Desktop, MiMo Code, and OpenRouter (with listed per-1M-token and cached-token pricing).
Kev, a GitHub repo for small Jev-like decision models, was released with local training and a TypeSafe System One–compatible API plus a web playground. The repo ships Kev models sized 0.8B, 4B, and 9B, including a note that Kev-4B and Kev-9B fit a 32 GB Mac. Users can run a local server, call /v1/systemone with multiple question types that return calibrated probabilities and confidence, and compare answer effects via permuting and isolation demos.
Xiaomi released the MiMo-V2.6 model family and published MiMo-V2.6-Pro’s weights on Hugging Face under an MIT license, claiming it as the top open-weight model on the Artificial Analysis Intelligence Index. MiMo-V2.6-Pro scored 46 points, up from 26 points for MiMo-V2.5-Pro. This raises the open-weight ceiling while establishing MiMo’s sparse mixture-of-experts models (plus Flash and UltraSpeed) as lower-cost options with updated availability and pricing for self-hosting and fine-tuning.
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