Open4bits / Ministral-3-3B-Base-2512-GGUF
This repository provides the Ministral 3 3B Base model converted to GGUF format, published by Open4bits to enable efficient local inference with reduced memory usage and broad CPU compatibility.
The underlying Ministral 3 model and architecture are developed and owned by Ministral. This repository contains only a quantized GGUF conversion of the original model weights.
The model is designed for lightweight, high-performance text generation and instruction-following tasks, making it well suited for local and resource-constrained environments.
Model Overview
Ministral 3 is a next-generation transformer-based large language model developed for strong generalization and robust natural language understanding.
This release uses the 3B parameter Base variant, optimized for general-purpose text generation, reasoning, and instruction compliance.
The GGUF format enables broad compatibility with popular local inference engines and efficient CPU-based runtimes.
Model Details
- Architecture: Ministral 3 Base
- Parameters: ~3 billion
- Format: GGUF (quantized)
- Task: Text generation, instruction following
- Weight tying: Preserved
- Compatibility: GGUF-compatible inference runtimes (CPU-focused)
Compared to larger models in the same family, this variant offers a favorable balance of performance and resource efficiency.
Intended Use
This model is intended for:
- Local text generation and conversational applications
- CPU-based or low-resource deployments
- Research, experimentation, and prototyping
- Self-hosted or offline AI systems
Limitations
- Reduced performance compared to larger or non-quantized variants
- Output quality depends on prompt engineering and inference settings
- Not specifically tuned for domain-specific or specialized tasks
License
This model is released under the original licensing terms of the base Ministral 3 model.
Users must comply with the licensing conditions defined by the original model creators.
Support
If you find this model useful, please consider supporting the project.
Your support enables Open4bits to continue releasing and maintaining high-quality, efficient open models for the community.
