GGUF
conversational
How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf g023/NeuronBlade-Qwen3.5-4B:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf g023/NeuronBlade-Qwen3.5-4B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf g023/NeuronBlade-Qwen3.5-4B:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf g023/NeuronBlade-Qwen3.5-4B: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 g023/NeuronBlade-Qwen3.5-4B:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf g023/NeuronBlade-Qwen3.5-4B: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 g023/NeuronBlade-Qwen3.5-4B:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf g023/NeuronBlade-Qwen3.5-4B:Q4_K_M
Use Docker
docker model run hf.co/g023/NeuronBlade-Qwen3.5-4B:Q4_K_M
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So this model is made by using (https://github.com/g023/neuronblade) to alter a Qwen3.5 4B model to improve effectiveness. It is a WIP so feel free to test with me. I will be updating as I go. MODEL CAN HAVE UNPREDICTABLE OUTPUTS

llama-cli -m NeuronBlade-Qwen3.5-4B-Q4_K_M.gguf -n 8192 --temp 1.0 --top-p 0.9 --repeat-last-n 16384 --mirostat 2 --mirostat-lr 0.2 --mirostat-ent 3 --presence-penalty 0.3 --frequency-penalty 0.5 --repeat-penalty 0.4
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GGUF
Model size
4B params
Architecture
qwen35
Hardware compatibility
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