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 falloutxvats/brain-vision:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf falloutxvats/brain-vision:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf falloutxvats/brain-vision:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf falloutxvats/brain-vision: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 falloutxvats/brain-vision:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf falloutxvats/brain-vision: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 falloutxvats/brain-vision:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf falloutxvats/brain-vision:Q4_K_M
Use Docker
docker model run hf.co/falloutxvats/brain-vision:Q4_K_M
Quick Links

brain-vision

Vision-language (image-text-to-text) GGUF quant for local multimodal inference.

Base model

Quantization

  • Quantized by mradermacher
  • Quant type: Q4_K_M
  • File: Qwen3-VL-8B-Instruct-abliterated.Q4_K_M.gguf

License

Follow the license of the base / source model repositories (Qwen / abliterated GGUF source).

Disclaimer

This is a redistributed GGUF quant. Weights were not trained or quantized here; they are mirrored from the mradermacher GGUF repository for convenience.

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qwen3vl
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