Instructions to use unsloth/Qwen3.5-35B-A3B-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 unsloth/Qwen3.5-35B-A3B-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 unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
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 unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
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 unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
Use Docker
docker model run hf.co/unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
- LM Studio
- Jan
- vLLM
How to use unsloth/Qwen3.5-35B-A3B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unsloth/Qwen3.5-35B-A3B-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": "unsloth/Qwen3.5-35B-A3B-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/unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
- Ollama
How to use unsloth/Qwen3.5-35B-A3B-GGUF with Ollama:
ollama run hf.co/unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
- Unsloth Desktop
- Pi
How to use unsloth/Qwen3.5-35B-A3B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
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": "unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use unsloth/Qwen3.5-35B-A3B-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
- Lemonade
How to use unsloth/Qwen3.5-35B-A3B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Qwen3.5-35B-A3B-GGUF-UD-Q4_K_XL
List all available models
lemonade list
- Hermes Agent
How to use unsloth/Qwen3.5-35B-A3B-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 unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
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 unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use unsloth/Qwen3.5-35B-A3B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL
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 "unsloth/Qwen3.5-35B-A3B-GGUF:UD-Q4_K_XL" \ --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"
Problem with UD-IQ3_XXS model loading in llama.cpp?
I downloaded the file for "Qwen3.5-35B-A3B-UD-IQ3_XXS" the sha256 matched but trying to load it into llama.cpp server gave the error:
srv load_model: loading model '.../Qwen3.5-35B-A3B-UD-IQ3_XXS.gguf'
common_init_result: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on
llama_model_load: error loading model: tensor 'blk.8.ffn_up_exps.weight' data is not within the file bounds, model is corrupted or incomplete
llama_model_load_from_file_impl: failed to load model
llama_params_fit: encountered an error while trying to fit params to free device memory: failed to load model
llama_params_fit: fitting params to free memory took 0.10 seconds
llama_model_load: error loading model: tensor 'blk.8.ffn_up_exps.weight' data is not within the file bounds, model is corrupted or incomplete
llama_model_load_from_file_impl: failed to load model
Perhaps this is a llama.cpp issue. However the larger file "Qwen3.5-35B-A3B-UD-IQ3_S" worked fine?
Closed. My mistake. The working directory should have contained a symbolic link but instead had a truncated file. The sha was from the downloaded copy on a data drive. My apologies.