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 sm54/deepseek-v4-flash-0731-gguf:F16
# Run inference directly in the terminal:
llama cli -hf sm54/deepseek-v4-flash-0731-gguf:F16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf sm54/deepseek-v4-flash-0731-gguf:F16
# Run inference directly in the terminal:
llama cli -hf sm54/deepseek-v4-flash-0731-gguf:F16
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 sm54/deepseek-v4-flash-0731-gguf:F16
# Run inference directly in the terminal:
./llama-cli -hf sm54/deepseek-v4-flash-0731-gguf:F16
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 sm54/deepseek-v4-flash-0731-gguf:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf sm54/deepseek-v4-flash-0731-gguf:F16
Use Docker
docker model run hf.co/sm54/deepseek-v4-flash-0731-gguf:F16
Quick Links

Built to run with antirez / ds4 inference engine. Not tested or built for llama cpp. Q4K available with dspark drafter.

Downloads last month
5,032
GGUF
Model size
284B params
Architecture
deepseek4
Hardware compatibility
Log In to add your hardware

16-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for sm54/deepseek-v4-flash-0731-gguf

Quantized
(172)
this model