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Model Library
Arcee AI
Poolside
MiMo V2.6 ProMiMo V2.6 Flash
Xiaomi MiMo
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  5. MiMo V2.6 Flash

MiMo V2.6 Flash

MiMo V2.6 Flash is a native omnimodal Mixture-of-Experts model designed for coding agents, computer use, cybersecurity, and long-horizon tasks across text, image, video, and audio. It features 309B total parameters with 15B activated, using a 48-layer architecture with 4,096 hidden size, 64 attention heads, and 8 KV heads. The architecture interleaves 39 Sliding Window Attention layers with 9 Global Attention layers, using 256 routed experts with 8 activated per token. Supporting a 1M-token context, it integrates vision and audio encoders with Multi-Token Prediction for efficient agentic inference.

Deploy with NVIDIA B200Contact Sales

About this model

PaperBlogHF Model Card

MiMo V2.6 Flash is a native omnimodal Mixture-of-Experts model designed for coding agents, computer use, cybersecurity, and long-horizon tasks across text, image, video, and audio. It features 309B total parameters with 15B activated, using a 48-layer architecture with 4,096 hidden size, 64 attention heads, and 8 KV heads. The architecture interleaves 39 Sliding Window Attention layers with 9 Global Attention layers, using 256 routed experts with 8 activated per token. Supporting a 1M-token context, it integrates vision and audio encoders with Multi-Token Prediction for efficient agentic inference.

Model Type

Omni Model

Released

September 22, 2026

License: MIT

Parameters

309B

Model ID
XiaomiMiMo/MiMo-V2.6-Flash-RL
Capabilities
Text GenerationInstruction FollowingReasoningMathematical ReasoningCode Generation+5

Model specifications and capabilities are published by the model author and reproduced here from Paper (XiaomiMiMo/MiMo-V2.6-Flash-RL). Released under MIT. Further reading: Blog · HF Model Card

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Hardware

B200

1,440 GB

Engine

vLLM
SGLang

Deployment code

INFERENCE COMMAND
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Requires vllm/vllm-openai:mimo-v26 or any standard vLLM image v0.30.0+ to support this model configuration.

Performance under load

115k92k69k46k23k0163264128256512Total Tokens / secConcurrent requests
Tokens/s (total)

Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.

SS

Shivam Sharma

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