How to Setup MiniMax-M2.5 PC with NPU 5-Minute Setup

How to Setup MiniMax-M2.5 PC with NPU 5-Minute Setup

Docker offers the quickest path to setting up this model locally.

Make sure to follow the instructions below.

The system automatically triggers a cloud download for all heavy weights.

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

🔍 Hash-sum: 77068ed73244b3770e36b9c6f6e9a038 | 🕓 Last update: 2026-06-24



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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