Xiaomi Details AI Models and Feature Portfolio
Gizmochina reports that Xiaomi has expanded its AI portfolio across language, reasoning, code, and voice technologies. The article says Xiaomi first entered the open-source LLM race in April 2025 with MiMo, a 7 billion-parameter model; Gizmochina reports the reinforcement-learning variant scored 95.8% on the MATH-500 benchmark and reportedly outperformed OpenAI's o1-mini and Alibaba's Qwen-32B-Preview on AIME 2024 and 2025. Gizmochina also reports the company released a larger MoE model, MiMo-V2-Flash, in December 2025, described as a 309 billion-parameter model with only 15 billion parameters active at inference, rivaling top-tier models on software-engineering tests while achieving 150 tokens per second and an inference cost reportedly at 2.5% of Claude's, with API input pricing reported at $0.1 per million input tokens. Gizmochina documents training corpus sizes, MIT licensing, Hugging Face availability, and credits Luo Fuli as development lead. The roundup also covers miclaw, a system-level autonomous agent built on MiMo-V2-Pro, and OmniVoice, an open-source multilingual voice cloning model supporting over 600 languages.
What happened
Gizmochina published a roundup documenting Xiaomi's full AI model portfolio as of June 2026. The article reports Xiaomi entered the open-source LLM race in April 2025 with `MiMo`, a 7 billion-parameter model released under an MIT license on Hugging Face. Gizmochina reports the reinforcement-learning variant of MiMo-7B scored 95.8% on the MATH-500 benchmark, reportedly outperforming OpenAI's o1-mini and Alibaba's Qwen-32B-Preview on AIME 2024 and 2025. The article credits Luo Fuli as development lead and reports training figures of 200 billion reasoning tokens across a 25 trillion-token corpus.
MiMo-V2-Flash
Gizmochina reports that `MiMo-V2-Flash`, released in December 2025, is a sparse Mixture-of-Experts model with 309 billion total parameters and roughly 15 billion active at inference -- a design that keeps per-inference compute low while maintaining large model capacity. Gizmochina reports the model ranked among the top two open-source models on reasoning benchmarks, rivaled Claude Sonnet 4.5 on SWE-Bench Verified software-engineering tests, achieved around 150 tokens per second, and priced API input at $0.1 per million tokens, described as roughly 2.5% of Claude's API cost. Weights and code are available on GitHub and Hugging Face under MIT license; an arXiv technical report (2601.02780) covers the architecture in detail.
miclaw and OmniVoice: The roundup also covers `miclaw`, a system-level autonomous AI assistant announced in March 2026 that embeds MiMo-V2-Pro into the device OS to control apps, navigate mobile browsers, and manage IoT devices. `OmniVoice`, open-sourced in May 2026, is a multilingual voice cloning model supporting over 600 languages with emotional transitions and regional dialect synthesis.
Benchmark verification
The cited performance and cost figures are Xiaomi-reported. Independent replication of the SWE-Bench Verified and AIME 2024/2025 results will be needed to confirm Xiaomi's claims.
Scoring Rationale
Single-source Gizmochina roundup summarising Xiaomi's LLM portfolio covering releases from April 2025 to May 2026. The underlying models were notable at release -- MiMo-V2-Flash's claimed cost-performance ratio rivaling Claude Sonnet 4.5 on SWE-Bench is significant if independently confirmed -- but this article is a retrospective explainer, not a new announcement. Solid-tier as a useful practitioner reference on an expanding open-weight model family.
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