Instructions to use unsloth/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf unsloth/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama cli -hf unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL
Use Docker
docker model run hf.co/unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL
- Llama new
- LM Studio
- Jan
- Ollama
How to use unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF with Ollama:
ollama run hf.co/unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL
- Unsloth Desktop
- Pi
How to use unsloth/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL
- Lemonade
How to use unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Devstral-Small-2-24B-Instruct-2512-GGUF-UD-Q4_K_XL
List all available models
lemonade list
- Hermes Agent
How to use unsloth/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-GGUF:UD-Q4_K_XL
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use unsloth/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-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/Devstral-Small-2-24B-Instruct-2512-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"
Please update llama.cpp to see improved performance!
Hey guys, please update llama.cpp to use the latest updates from 2 days ago. According to many of people and our tests, you should see large improvements in Devstral 2 etc for use cases like tool calling as well. Looping should be also less.
We'll be reconverting today and all should be reuploaded by tomorrow.
See these 2 pull requests and issues:
https://github.com/ggml-org/llama.cpp/pull/17945
https://github.com/ggml-org/llama.cpp/issues/17980
when can we tell that its been updated?
just testing some arbitrary PHP code with Devstral 2 Small, Roo code and updated llama.cpp, works great so far (also better than Qwen3 Coder and Devstral 2507)
tested in roo code for a tetris game, it worked, no errors
tested in roo code for a tetris game, it worked, no errors
What backend do you use? I can't get roocode to work, telling me it doesn't support tool calling...
Tried koboldcpp with jinja and jinja for tools enabled:
The model returned no assistant messages. This may indicate an issue with the API or the model's output. - koboldcpp over OpenAI Compatible
Date/time: 2026-01-10T17:03:04.836Z
Extension version: 3.39.2
Provider: ollama
Model: MODELFILE
The model provided text/reasoning but did not call any of the required tools. This usually indicates the model misunderstood the task or is having difficulty determining which tool to use. The model has been automatically prompted to retry with proper tool usage. - koboldcpp over ollama
and ollama afterwards with the same file and:
PARAMETER num_ctx 65536
PARAMETER temperature 0.7
If you're using ollama, which quant did you use and did you install it through ollama itself?
If you're using llamacpp, can you tell me how? I've never served a model using it.
I barely use llamacpp/ollama only tabbyapi/koboldcpp