Model ID
XiaomiMiMo/MiMo-V2.6-Pro-RL
Capabilities
MiMo V2.6 Pro
MiMo V2.6 Pro is an ultra-large omnimodal Mixture-of-Experts model designed for coding agents, computer use, cybersecurity, and long-horizon tasks across text, image, video, and audio. It features 1.02T total parameters with 42B activated, using a 70-layer architecture with 6,144 hidden size, 128 attention heads, and 8 KV heads. The architecture interleaves 60 Sliding Window Attention layers with 10 Global Attention layers, using 384 routed experts with 8 activated per token. Supporting a 1M-token context, it integrates vision and audio encoders with Multi-Token Prediction for demanding agentic workloads.
About this model
MiMo V2.6 Pro is an ultra-large omnimodal Mixture-of-Experts model designed for coding agents, computer use, cybersecurity, and long-horizon tasks across text, image, video, and audio. It features 1.02T total parameters with 42B activated, using a 70-layer architecture with 6,144 hidden size, 128 attention heads, and 8 KV heads. The architecture interleaves 60 Sliding Window Attention layers with 10 Global Attention layers, using 384 routed experts with 8 activated per token. Supporting a 1M-token context, it integrates vision and audio encoders with Multi-Token Prediction for demanding agentic workloads.
Model specifications and capabilities are published by the model author and reproduced here from Paper (XiaomiMiMo/MiMo-V2.6-Pro-RL). Released under MIT. Further reading: Blog · HF Model Card
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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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
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.
NVIDIA HGX B200
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