Instructions to use unsloth/Kimi-K2-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/Kimi-K2-Instruct-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unsloth/Kimi-K2-Instruct-GGUF", dtype="auto") - llama-cpp-python
How to use unsloth/Kimi-K2-Instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="unsloth/Kimi-K2-Instruct-GGUF", filename="BF16/Kimi-K2-Instruct-BF16-00001-of-00045.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use unsloth/Kimi-K2-Instruct-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf unsloth/Kimi-K2-Instruct-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/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf unsloth/Kimi-K2-Instruct-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/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Use Docker
docker model run hf.co/unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use unsloth/Kimi-K2-Instruct-GGUF with Ollama:
ollama run hf.co/unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
- Unsloth Studio
How to use unsloth/Kimi-K2-Instruct-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/Kimi-K2-Instruct-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/Kimi-K2-Instruct-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/Kimi-K2-Instruct-GGUF to start chatting
- Pi
How to use unsloth/Kimi-K2-Instruct-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
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/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use unsloth/Kimi-K2-Instruct-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf unsloth/Kimi-K2-Instruct-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/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Run Hermes
hermes
- Docker Model Runner
How to use unsloth/Kimi-K2-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
- Lemonade
How to use unsloth/Kimi-K2-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Kimi-K2-Instruct-GGUF-UD-Q4_K_XL
List all available models
lemonade list
New updates: Correct system prompt, Tool calling, more fixes & llama.cpp!
Update: We recently informed the Kimi team about the correct system prompts and they were quick to address the issue. Now we reuploaded all of the quants to use these new changes.
More info about the fixes: https://x.com/danielhanchen/status/1946163064665260486
If you want to use these new changes, you must redownload the quants
Hey guys yesterday llama.cpp added in the PR for Kimi so you can now run it directly with llama.cpp's latest version.
Tool calling also got updated as at 16th July 2025 -
Dec 29th 2025: Update - Just some git squashing to clear some disk space on our organization