# Kimi K3 License > Source: > Published: 2026-07-27 15:13:26+00:00 Image-Text-to-Text Transformers Safetensors kimi_k3 feature-extraction compressed-tensors custom_code ### Instructions to use moonshotai/Kimi-K3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started. - Libraries [Transformers](/moonshotai/Kimi-K3?library=transformers)How to use moonshotai/Kimi-K3 with Transformers: ``` python # Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="moonshotai/Kimi-K3", trust_remote_code=True) python # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("moonshotai/Kimi-K3", trust_remote_code=True, device_map="auto") ``` - Notebooks [Google Colab](/moonshotai/Kimi-K3/colab)[Kaggle](/moonshotai/Kimi-K3/kaggle)- Local Apps [Settings](/settings/local-apps) [vLLM](/moonshotai/Kimi-K3?local-app=vllm)How to use moonshotai/Kimi-K3 with vLLM: ##### Install from pip and serve model ``` # Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "moonshotai/Kimi-K3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "moonshotai/Kimi-K3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' ``` ##### Use Docker ``` docker model run hf.co/moonshotai/Kimi-K3 ``` [SGLang](/moonshotai/Kimi-K3?local-app=sglang)How to use moonshotai/Kimi-K3 with SGLang: ##### Install from pip and serve model ``` # Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "moonshotai/Kimi-K3" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "moonshotai/Kimi-K3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' ``` ##### Use Docker images ``` docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "moonshotai/Kimi-K3" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "moonshotai/Kimi-K3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' ``` [Docker Model Runner](/moonshotai/Kimi-K3?local-app=docker-model-runner)How to use moonshotai/Kimi-K3 with Docker Model Runner: ``` docker model run hf.co/moonshotai/Kimi-K3 ``` | Kimi K3 License | | | Copyright (c) 2026 Moonshot AI | | | Permission is hereby granted, free of charge, to any person (the "Licensee") | | | obtaining a copy of this software — including the model weights, parameters, | | | configuration files, inference and training code, and associated documentation | | | (collectively, the "Software") — to deal in the Software without restriction. | | | This includes, without limitation, the rights to use, copy, modify, merge, | | | publish, distribute, sublicense, and/or sell copies of the Software; to run, | | | deploy, fine-tune, or otherwise modify the Software and create derivative works | | | from it; and to permit persons to whom the Software is furnished to do so, in | | | each case subject to the following conditions: | | | 1. 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