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 mcmonkey/Flux2MistralGGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mcmonkey/Flux2MistralGGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mcmonkey/Flux2MistralGGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mcmonkey/Flux2MistralGGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf mcmonkey/Flux2MistralGGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf mcmonkey/Flux2MistralGGUF:Q4_K_M
Use Docker
docker model run hf.co/mcmonkey/Flux2MistralGGUF:Q4_K_M
Quick Links

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

Literally just https://huggingface.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF/blob/main/Mistral-Small-3.2-24B-Instruct-2506-Q4_K_M.gguf but blocks after 29 removed so it can be used as the Flux2 tenc, saves about 3-ish gigabytes of space over the unsloth copy.

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GGUF
Model size
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Architecture
llama
Hardware compatibility
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