Instructions to use gabriellarson/Kimi-Dev-72B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gabriellarson/Kimi-Dev-72B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="gabriellarson/Kimi-Dev-72B-GGUF",
	filename="Kimi-Dev-72B-Q2_K.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use gabriellarson/Kimi-Dev-72B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf gabriellarson/Kimi-Dev-72B-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 gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf gabriellarson/Kimi-Dev-72B-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 gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use gabriellarson/Kimi-Dev-72B-GGUF with Ollama:
```
ollama run hf.co/gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use gabriellarson/Kimi-Dev-72B-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 gabriellarson/Kimi-Dev-72B-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 gabriellarson/Kimi-Dev-72B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for gabriellarson/Kimi-Dev-72B-GGUF to start chatting

Pi new

How to use gabriellarson/Kimi-Dev-72B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf gabriellarson/Kimi-Dev-72B-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": "gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use gabriellarson/Kimi-Dev-72B-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 gabriellarson/Kimi-Dev-72B-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 gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use gabriellarson/Kimi-Dev-72B-GGUF with Docker Model Runner:
```
docker model run hf.co/gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M
```

Lemonade

How to use gabriellarson/Kimi-Dev-72B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull gabriellarson/Kimi-Dev-72B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Kimi-Dev-72B-GGUF-Q4_K_M

List all available models

lemonade list

Introducing Kimi-Dev:
A Strong and Open-source Coding LLM for Issue Resolution

Kimi-Dev Team

📄 Tech Report (Coming soon...) | 📄 Github

We introduce Kimi-Dev-72B, our new open-source coding LLM for software engineering tasks. Kimi-Dev-72B achieves a new state-of-the-art on SWE-bench Verified among open-source models.

Kimi-Dev-72B achieves 60.4% performance on SWE-bench Verified. It surpasses the runner-up, setting a new state-of-the-art result among open-source models.
Kimi-Dev-72B is optimized via large-scale reinforcement learning. It autonomously patches real repositories in Docker and gains rewards only when the entire test suite passes. This ensures correct and robust solutions, aligning with real-world development standards.
Kimi-Dev-72B is available for download and deployment on Hugging Face and GitHub. We welcome developers and researchers to explore its capabilities and contribute to development.

Performance of Open-source Models on SWE-bench Verified.

Citation

@misc{kimi_dev_72b_2025,
  title        = {Introducing Kimi-Dev: A Strong and Open-source Coding LLM for Issue Resolution},
  author       = {{Kimi-Dev Team}},
  year         = {2025},
  month        = {June},
  url          = {\url{https://www.moonshot.cn/Kimi-Dev}}
}

Downloads last month: 649

GGUF

Model size

73B params

Architecture

qwen2

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for gabriellarson/Kimi-Dev-72B-GGUF

Base model

Qwen/Qwen2.5-72B

Finetuned

moonshotai/Kimi-Dev-72B

Quantized

(24)

this model