Instructions to use unsloth/diffusiongemma-26B-A4B-it-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/diffusiongemma-26B-A4B-it-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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf unsloth/diffusiongemma-26B-A4B-it-GGUF: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 unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf unsloth/diffusiongemma-26B-A4B-it-GGUF: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 unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
Use Docker
docker model run hf.co/unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use unsloth/diffusiongemma-26B-A4B-it-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unsloth/diffusiongemma-26B-A4B-it-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/diffusiongemma-26B-A4B-it-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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
- Ollama
How to use unsloth/diffusiongemma-26B-A4B-it-GGUF with Ollama:
ollama run hf.co/unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
- Unsloth Studio
How to use unsloth/diffusiongemma-26B-A4B-it-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unsloth/diffusiongemma-26B-A4B-it-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unsloth/diffusiongemma-26B-A4B-it-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/diffusiongemma-26B-A4B-it-GGUF to start chatting
- Pi
How to use unsloth/diffusiongemma-26B-A4B-it-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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use unsloth/diffusiongemma-26B-A4B-it-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
- Lemonade
How to use unsloth/diffusiongemma-26B-A4B-it-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.diffusiongemma-26B-A4B-it-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use unsloth/diffusiongemma-26B-A4B-it-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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use unsloth/diffusiongemma-26B-A4B-it-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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M
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/diffusiongemma-26B-A4B-it-GGUF:Q4_K_M" \ --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"
You can now Run DiffusionGemma in Unsloth Studio UI ✨
I have a 5090, and after loading the DiffusionGemma (Q4) model, I only have a max context window of 8192 tokens. My GPU isn't even full; it's sitting at 28/32 GB used. In addition, I have 128 GB of RAM which is not being used. I'm not sure what is happening, but every time I try to set the context beyond 8k and reset, it reverts back to 8k.
im on 5090 - https://gist.github.com/johndpope/5aa9af3edd22cbe3dd28ab2719081916 if you just want to play - you can use vllm + docker - this works - for 3090 - i couldn't get it working...
(it will fill up your local hf cache if you monitor it - first boot will take forever to cache llm)
it doesnt accept images ask for mmproj file. you are misleading people if its so. unsloth latest, model redownloaded q4, text running even tried to built from source the exac ggml llam cpp pr.. no way..
No tool calls for unsloth/diffusiongemma-26B-A4B-it-GGUF in Unsloth Studio
I tried unsloth/diffusiongemma-26B-A4B-it-GGUF (unsloth, Q8_0) model with Unsloth studio (2026.6.9) - after model is loaded "code", "search", "mcp" - all gets disabled. Model card in Hub shows "Image Text To Text", "Vision", "Conversational" - but nothing like "tool use"
