What is FastChat?
FastChat is the open-source platform behind LMSYS Chatbot Arena — the most-cited LLM evaluation benchmark in the world. Released by the LMSYS team (UC Berkeley, CMU, Stanford, UC San Diego, MBZUAI) in March 2023, FastChat provides a complete framework for training, serving, and evaluating large language models.
It's released under Apache 2.0 and is the de-facto standard for deploying open chatbots with OpenAI-compatible APIs.
Why FastChat Is Trending in 2026
FastChat has become the go-to deployment platform for self-hosted LLMs because of its OpenAI API compatibility. Drop-in replace your OpenAI client with a FastChat endpoint — your existing code keeps working with Llama 3, Mistral, Qwen, or any other open model.
FastChat also powers the famous Chatbot Arena leaderboard at lmarena.ai, where models are anonymously ranked through human-preference voting.
Key Features and Capabilities
FastChat provides multi-model serving with vLLM and SGLang backends, OpenAI-compatible REST API, web UI for chatting, model evaluation tools, model fine-tuning scripts (LoRA/full FT), and the Chatbot Arena framework.
Who Should Use FastChat?
FastChat is built for AI engineers, ML platform teams, researchers, and startups deploying open LLMs in production with maximum compatibility and ease.
Top Use Cases
Real-world applications include self-hosted ChatGPT alternatives, internal company chatbots, multi-model evaluation pipelines, A/B testing different LLMs, OpenAI API drop-in replacements, fine-tuning workflows, and LMSYS-style benchmarking.
Where Can You Run It?
FastChat runs on any Linux/Mac server with Python and CUDA. Container images are available for Docker and Kubernetes. It supports multi-GPU serving with vLLM, SGLang, or HuggingFace Transformers backends.
How to Use FastChat (Quick Start)
Install: pip install 'fschat[model_worker,webui]'. Launch a controller, model worker, and OpenAI API server: python -m fastchat.serve.controller, python -m fastchat.serve.model_worker --model-path lmsys/vicuna-7b-v1.5, python -m fastchat.serve.openai_api_server.
Now point any OpenAI client at http://localhost:8000/v1 — it just works.
When Should You Choose FastChat?
Choose FastChat when you need a battle-tested, OpenAI-compatible, multi-model serving platform. For pure-speed inference, vLLM standalone or SGLang are faster. For larger production deployments, consider Hugging Face TGI or NVIDIA Triton.
Pricing
FastChat is completely free under Apache 2.0.
Pros and Cons
Pros: ✔ Apache 2.0 license ✔ OpenAI-compatible API ✔ Powers Chatbot Arena ✔ Multi-model serving ✔ vLLM/SGLang backends ✔ Active LMSYS development
Cons: ✘ Some operations slower than raw vLLM ✘ Production scaling needs care ✘ Less polished UI than commercial tools
Final Verdict
FastChat is the open-source serving backbone of the modern LLM ecosystem — essential infrastructure for anyone running open chatbots in 2026. Discover more LLM tools at FreeAPIHub.com.