| Type | MoE LLM |
| Capabilities | Text Generation, Instruction Following, Reasoning, Mathematical Reasoning+5 more |
| Release Date | 28 April, 2026 |
| Links | |
| License | MIT |
Inference Instructions
Deploy and run this model on NVIDIA B200 GPUs using the command below. Copy the command to get started with inference.
CONSOLE
docker run -it --rm --runtime=nvidia --gpus all --ipc=host --shm-size=128g -p 8000:8000 -v ~/.cache/huggingface:/root/.cache/huggingface -e HF_TOKEN='YOUR_HF_TOKEN' vllm/vllm-openai:mimov25-cu130 XiaomiMiMo/MiMo-V2.5-Pro --tensor-parallel-size 8 --enable-expert-parallel --max-model-len auto --gpu-memory-utilization 0.90 --max-num-seqs 1024 --enable-auto-tool-choice --reasoning-parser mimo --tool-call-parser mimo --generation-config vllm --trust-remote-code
Note
For MiMo V2.5 Pro support, use vllm/vllm-openai:mimov25-cu130 for CUDA 13, vllm/vllm-openai:mimov25-cu129 for CUDA 12.9, or any subsequent official vLLM release.
Model Benchmarks
Each model was tested with a fixed input size and total token volume while increasing concurrency to measure serving performance under load.
ITL vs Concurrency
Time to First Token
Throughput Scaling
Total Tokens/sec vs Avg TTFT
Vultr Cloud GPU
NVIDIA HGX B200
Deploy NVIDIA B200 on Vultr Cloud GPU