The shortest path to running this model is by activating Hyper-V features.
Check out the detailed setup guide below to begin.
The installer auto-downloads and deploys the entire model pack.
The deployment tool scans your environment and chooses the ideal parameters.
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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- Launch MiniMax-M2.5
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- Patch tuning Mistral-Large-Instruct parameters for low-latency private servers
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- Installer deploying local internet-free web scraping tools with built-in vision parsing blocks
- MiniMax-M2.5 on AMD/Nvidia GPU Easy Build FREE
