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 kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
# Run inference directly in the terminal:
llama cli -hf kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
# Run inference directly in the terminal:
llama cli -hf kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
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 kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
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 kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
Use Docker
docker model run hf.co/kabachuha/Gemma-4-The-Deckards-Brain-31B-GGUF:
Quick Links

The DECKARD's Brain - Gemma 4, 31b - GGUF

GGUF-quantized version of kabachuha/Gemma-4-The-Deckards-Brain-31B, a merge of two heretic Gemma 4 31B dense models with thinking capabilities.

The GGUF-converted native NVFP4 file was obtained through llama.cpp's convert_hf_to_gguf.py from the r/writingprompts calibrated base of https://huggingface.co/kabachuha/Gemma-4-The-Deckards-Brain-31B-NVFP4.

The prompt format is fully inherited from DavidAU's The Deckard Thinking, meaning the chat template will have thinking by default. To disable, override the chat template with chat_template-instruct.jinja.

Thinking is highly recommended to not be ever turned off! If you are role-playing in non-English, this is crucial to bring your language output distribution closer to the English/Japanese training set, otherwise it will be much more bland and more censored!

For the rest of the information, see the original model card.

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gemma4
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