Run Ministral-3-3B-Instruct-2512 Quantized GGUF

If you need a near-instant local setup, just fetch files via a basic curl request.

Go through the configuration rules shown below.

Everything happens automatically, including the heavy cloud asset download.

The installer will automatically analyze your hardware and select the optimal configuration.

💾 File hash: a5fc1db5c68779e86ef3a2aca9e603c5 (Update date: 2026-06-29)
  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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.

Specification Value
Parameter Count 3 B
Context Length 8 K tokens
Inference Speed ≈250 tokens/s on GPU
Training Data Size ≈1.5 TB of text
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