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Ministral-3-3B-Instruct-2512 No Python Required

The fastest way to get this model running locally is via Docker.

Use the instructions provided below to complete the setup.

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

🔍 Hash-sum: d21c148a3587812934eaa1e88ec3f69b | 🕓 Last update: 2026-06-28



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The **Ministral-3-3B-Instruct-2512** is a compact yet powerful language model designed for high‑efficiency inference in production environments. It leverages a refined instruction‑following architecture that enables *precise* task execution across a wide range of textual prompts. With **3 billion parameters**, the model balances performance and resource consumption, delivering competitive benchmark scores while maintaining a small memory footprint. Its **multilingual capabilities** support over 50 languages, making it suitable for global applications that require consistent comprehension and generation. The table below captures the core technical specifications that highlight its speed and scalability. Overall, the Ministral-3-3B-Instruct-2512 offers an *i*state-of-the-art* experience for developers seeking a lightweight yet capable AI assistant.

SpecificationValue
Parameter Count3 B
Context Length8 K tokens
Inference Speed≈250 tokens/s on GPU
Training Data Size≈1.5 TB of text
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