Deploy MiniMax-M2.5 Windows 11 Full Speed NPU Mode

Deploy MiniMax-M2.5 Windows 11 Full Speed NPU Mode

The fastest method for installing this model locally is by using Docker.

Refer to the instructions below to proceed.

The installer auto-downloads and deploys the entire model pack.

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

🗂 Hash: 40184c76814b67387294b68fd7d6dbdaLast Updated: 2026-06-26



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

MiniMax-M2.5 is an next‑generation transformer-based AI model designed for both textual and visual tasks. It leverages a sparse attention mechanism to achieve high inference speed while maintaining state‑of‑the‑art accuracy across benchmarks. The architecture incorporates a mixture‑of‑experts routing strategy, allowing efficient scaling to 175 billion parameters without a proportional increase in computational cost. Its training pipeline utilizes a curated web‑scale corpus combined with multimodal datasets, enabling robust context understanding and generation in multiple languages. The model’s energy‑efficient design reduces inference latency, making it suitable for deployment on edge devices and cloud services alike. Below is a concise comparison of key technical specifications:

Spec Value
Parameter Count 175 B
Context Length 8K tokens
Training Data Size 1.5 TB
Inference Speed >200 tokens/s
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