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Model details

MiMo-V2.5

MiMo-V2.5 sits inside Xiaomi's MiMo family of open-weights models aimed at developers who need strong reasoning and coding behavior in a deployable package. Xiaomi announced the lineup's flagship, MiMo-V2.5-Pro, as a 1.02T-parameter Mixture-of-Experts model with 42B active parameters, built on a hybrid-attention architecture and a one-the cataloged API limit. The base MiMo-V2.5 sits a step below the Pro variant, sharing the family emphasis on long-horizon coherence and software-engineering ability. Its headlining benchmark, MiMo Coding Bench, is reported at 68.4 for the Pro release, with the broader family positioned against other frontier general and coding systems.

In practical terms, MiMo-V2.5 is geared toward agentic applications, complex software engineering, and long-horizon tasks where maintaining context over very long inputs matters. The model accepts text, images, audio, and video as input and produces text output, supports tool calling, streaming, and structured reasoning, and is delivered with an open-weights license that lets teams self-host or integrate it through third-party APIs. A free public variant exposes these same capabilities with rate limits suitable for experimentation, making it a practical choice for prototype agents, code assistants, and multimodal pipelines that benefit from extended context and explicit reasoning support.

LLMTRmimo/mimo-v2.5mimo

Quick Info

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Provider
LLMTR
Model key
mimo/mimo-v2.5
Release date
Apr 22, 2026
Last updated
Apr 22, 2026
Knowledge cutoff
2024-12
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.14
Output token cost
$0.28

Limits

Output tokens
131,072 tokens
Context window
1,000,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about MiMo-V2.5

LLMTR

CoverageBenchmark

A community-authored thread on the NVIDIA DGX Spark / GB10 developer forum details a reproducible recipe for running the lukealonso/MiMo-V2.5-NVFP4 quantized checkpoint of MiMo-V2.5 on a 2x DGX Spark cluster with tensor parallelism. The setup uses vLLM 0.21.1rc1.dev39 on CUDA 13.2, instanttensor load format, Triton Att The BenchLM.ai model record for MiMo-V2.5 lists it as a proprietary model released on April 22, 2026 with a 1M-token context window and a composite capability score of 60.7/100, ranking 63rd out of 232 tracked models. The page surfaces 15 source-displayable benchmark rows, with the strongest eligible category being Mul

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