How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf llmware/mistral-3.2-24b-gguf:Q4_K_M
Use Docker
docker model run hf.co/llmware/mistral-3.2-24b-gguf:Q4_K_M
Quick Links

mistral-3.2-24b-gguf

mistral-3.2-24b-gguf is a GGUF Q4_K_M quantized version of mistral-3.2-24b, which is a 24B general purpose chat/instruct model from Mistral.

Model Description

  • Developed by: mistralai
  • Quantized by: llmware
  • Model type: mistral-3.2-24b
  • Parameters: 24 billion
  • Model Parent: mistralai/Mistral-Small-3.2-24B-Instruct-2506
  • Language(s) (NLP): English
  • License: Apache 2.0
  • Uses: General use
  • Quantization: int4

Model Card Contact

llmware on github

llmware on hf

llmware website

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GGUF
Model size
24B params
Architecture
llama
Hardware compatibility
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