meta:
  title: "MiMo-V2.5-Pro"
  slug: "mimo-v2-5-pro"
  provider: "MiMo (Xiaomi)"
  description: "Xiaomi's flagship MoE reasoning model (1.02T total / 42B active) with hybrid attention, native FP8 weights, and Multi-Token Prediction"
  date_added: 2026-04-27
  date_updated: 2026-04-27
  tasks:
    - text
  related_recipes:
    - "XiaomiMiMo/MiMo-V2.5"
  hardware:
    h200: verified

model:
  model_id: "XiaomiMiMo/MiMo-V2.5-Pro"
  min_vllm_version: "0.21.0"
  architecture: moe
  parameter_count: "1T"
  active_parameters: "42B"
  context_length: 1048576
  base_args:
    - "--trust-remote-code"
    - "--max-model-len auto"
    - "--generation-config"
    - "vllm"
  base_env: {}

features:
  tool_calling:
    description: "MiMo tool-call parser"
    args:
      - "--tool-call-parser"
      - "mimo"
      - "--enable-auto-tool-choice"
  reasoning:
    description: "MiMo reasoning parser"
    args:
      - "--reasoning-parser"
      - "mimo"
  spec_decoding:
    description: "Multi-Token Prediction"
    args:
      - "--speculative-config"
      - '{"method":"mtp","num_speculative_tokens":1}'

opt_in_features:
  - spec_decoding

variants:
  default:
    precision: fp8
    vram_minimum_gb: 1224
    description: "Native FP8 weights (block-wise e4m3 128x128); 8x H200 with TP8"
    extra_args:
      - "--tensor-parallel-size"
      - "8"
      - "--gpu-memory-utilization"
      - "0.95"
      - "--max-model-len"
      - "auto"

compatible_strategies:
  - single_node_tp
  - single_node_tep
  - pd_cluster

hardware_overrides: {}
strategy_overrides: {}

guide: |
  ## Overview

  MiMo-V2.5-Pro is Xiaomi's flagship MoE reasoning model with 1.02T total parameters
  and 42B active per token. It uses 384 routed experts (top-8) with hybrid
  attention (full-attention + sliding-window 128 at 6:1 ratio) over 70 layers
  (1 dense + 69 MoE) and ships with native FP8 (block-wise e4m3) weights.
  A 3-layer Multi-Token Prediction (MTP) head enables speculative decoding for
  ~3x output speed.

  ## Prerequisites

  - Hardware: 8x H200 (TP8)

  ### Pull the vLLM docker image

  Stable vLLM does not yet support MiMo V2.5. Use the pre-built image:

  ```bash
  docker pull vllm/vllm-openai:mimov25-cu129
  ```

  ## Launch commands

  Single-node TP8 (H200):

  ```bash
  vllm serve XiaomiMiMo/MiMo-V2.5-Pro \
    --tensor-parallel-size 8 \
    --trust-remote-code \
    --gpu-memory-utilization 0.95 \
    --max-model-len auto \
    --generation-config vllm
  ```

  With tool calling + reasoning:

  ```bash
  vllm serve XiaomiMiMo/MiMo-V2.5-Pro \
    --tensor-parallel-size 8 \
    --trust-remote-code \
    --gpu-memory-utilization 0.95 \
    --max-model-len auto \
    --reasoning-parser mimo \
    --tool-call-parser mimo \
    --enable-auto-tool-choice \
    --generation-config vllm
  ```

  ## Client Usage

  ```bash
  curl -X POST http://localhost:8000/v1/chat/completions \
    -H "Content-Type: application/json" \
    -d '{
      "model": "XiaomiMiMo/MiMo-V2.5-Pro",
      "messages": [{"role": "user", "content": "Hello MiMo!"}],
      "chat_template_kwargs": {"enable_thinking": true}
    }'
  ```

  Set `"enable_thinking": false` (or omit the kwargs) to disable thinking mode.


  ## References

  - [MiMo-V2.5-Pro on Hugging Face](https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Pro)