Mistral-Small-3.1-24B-Instruct-2503-Q4_K_M-GGUF
| Property | Value |
|---|---|
| Original Model | mistralai/Mistral-Small-3.1-24B-Instruct-2503 |
| Format | GGUF (Q4_K_M quantization) |
| Size | 24B parameters |
| Repository | HuggingFace |
What is Mistral-Small-3.1-24B-Instruct-2503-Q4_K_M-GGUF?
This is a quantized version of Mistral's 24B parameter instruction-tuned language model, converted to the GGUF format for efficient local deployment. The model uses Q4_K_M quantization to reduce its size while maintaining performance, making it suitable for running on consumer hardware through llama.cpp.
Implementation Details
The model was converted from the original Mistral format to GGUF using llama.cpp via the ggml.ai's GGUF conversion pipeline. This conversion enables efficient local inference while preserving the model's core capabilities.
- Optimized Q4_K_M quantization for balanced performance and size
- Compatible with llama.cpp for local deployment
- Supports both CLI and server deployment modes
- Context window of 2048 tokens (as configured in server mode)
Core Capabilities
- Full instruction-following capabilities of the original Mistral model
- Local inference without cloud dependencies
- Efficient memory usage through quantization
- Flexible deployment options via llama.cpp
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient quantization that enables running a 24B parameter model locally while maintaining good performance through the Q4_K_M compression scheme and GGUF format optimization.
Q: What are the recommended use cases?
The model is ideal for users who need to run a powerful language model locally, particularly in scenarios requiring privacy, offline access, or custom deployment configurations through llama.cpp. It's suitable for both CLI applications and server deployments.
