Instructions to use stepfun-ai/Step-3.7-Flash-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use stepfun-ai/Step-3.7-Flash-GGUF with 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 stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
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 stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
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 stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
Use Docker
docker model run hf.co/stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
- LM Studio
- Jan
- vLLM
How to use stepfun-ai/Step-3.7-Flash-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stepfun-ai/Step-3.7-Flash-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stepfun-ai/Step-3.7-Flash-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
- Ollama
How to use stepfun-ai/Step-3.7-Flash-GGUF with Ollama:
ollama run hf.co/stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
- Unsloth Desktop
- Pi
How to use stepfun-ai/Step-3.7-Flash-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use stepfun-ai/Step-3.7-Flash-GGUF with Docker Model Runner:
docker model run hf.co/stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
- Lemonade
How to use stepfun-ai/Step-3.7-Flash-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
Run and chat with the model
lemonade run user.Step-3.7-Flash-GGUF-Q4_K_S
List all available models
lemonade list
- Hermes Agent
How to use stepfun-ai/Step-3.7-Flash-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use stepfun-ai/Step-3.7-Flash-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_S" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
How to use the mtp gguf file in llama -server
How to use the mtp gguf file in llama -server ? any comment on how to properly set up the mtp part
Upload Step3.7-flash-mtp-BF16.gguf
Step3.7-flash-mtp-Q8_0.gguf??
You can try the following command:
./llama-server \
-m Step-3.7-Q4_K_S.gguf \
--spec-type draft-mtp \
--spec-draft-model Step3.7-flash-mtp-Q8_0.gguf \
-c 35000 \
-np 1 \
-b 2048 \
-ub 1024 \
--temp 0 \
--spec-draft-n-max 3 \
--spec-draft-p-min 0.06 \
--host 127.0.0.1 \
--port 8080
I’m not getting any increase in speed on my Mac with MTP. Is this something you’re seeing on your end as well?
Also, really looking forward to next model from this team
@MilestoneCap Yeah, MTP may not give much of a speedup on mac right now. It’s partly due to how MoE models work and partly the backend implementation. llama.cpp is still working on optimizations here.
And for the next model — shouldn’t be too long :)
@MilestoneCap Yeah, MTP may not give much of a speedup on mac right now. It’s partly due to how MoE models work and partly the backend implementation. llama.cpp is still working on optimizations here.
And for the next model — shouldn’t be too long :)
Awesome, hope it's still 128GB friendly. 3.7 was my favorite model to run locally until a few weeks ago