FastChat is a production-grade distributed serving platform for large language models that powers Chatbot Arena (lmarena.ai), handling 10M+ requests across 70+ models. The architecture centers on a controller that manages model worker registration, heartbeats, and request dispatching; model workers host models via multiple backends (HuggingFace transformers, vLLM, LightLLM, MLX, ExLlamaV2, xFasterTransformer, GPTQ, AWQ, dash-infer); an OpenAI-compatible RESTful API server routes chat/completion/embedding requests; and Gradio web UIs provide single-model chat and side-by-side battle interfaces. The codebase includes training pipelines for Vicuna/FastChat-T5 with FSDP/DeepSpeed/LoRA/QLoRA support, an MT-bench evaluation framework with LLM-as-a-judge (GPT-4), and data processing utilities for ShareGPT conversation cleaning. Key strengths: clean model adapter pattern for adding new architectures, extensible conversation template system, robust streaming API implementation, and well-integrated quantization backends. The system demonstrates non-obvious engineering in distributed inference coordination, attention optimization monkey patches, and multi-backend model loading abstraction.