MiMo V2.6 Pro (DeepInfra)

MiMo V2.6 Pro serves as the flagship of Xiaomi's MiMo-V2.6 series, built as a sparse Mixture-of-Experts model with roughly 1.02 trillion total parameters and around 42 billion parameters activated per inference. This design lets the model draw on broad expert capacity while keeping the per-token compute footprint closer to that of much smaller dense models, which is useful for workloads that need deep reasoning without paying full dense inference costs. The model is trained with large-scale mixed reinforcement learning, signaling an emphasis on alignment with complex tasks and tool-style interaction patterns rather than purely next-token language modeling.

MiMo V2.6 Pro is positioned as a natively omnimodal system that handles text, images, video, and audio as inputs and produces text outputs, with a one-million-token context window for long-form understanding across mixed media. That combination makes it a fit for agentic and reasoning-heavy applications where a single model has to ingest lengthy documents, screenshots, clips, or spoken material and reason across them in one pass. Open weights availability further supports local fine-tuning, evaluation, and deployment scenarios where teams want to adapt the model to domain-specific multimodal pipelines.