Xinference is a production-grade model serving platform that provides OpenAI-compatible REST APIs for a wide range of AI models including LLMs, embeddings, rerank, image generation, video, audio/TTS, and world models. It supports multiple inference backends (vLLM, SGLang, transformers, MLX, llama.cpp) and can be deployed as a single process or a distributed cluster using an actor-based supervisor/worker architecture (xoscar). The system includes a web UI for model management, authentication/authorization with OAuth2 scopes, token-aware routing for load balancing, and monitoring capabilities. It bundles many third-party model implementations for turnkey deployment, which reduces setup friction but introduces maintenance overhead from vendored code. The architecture is a hybrid of a monolithic FastAPI server and a distributed actor system. Key entry points are CLI commands (xinference, xinference-supervisor, xinference-worker) and the REST API. The frontend is a Next.js application statically exported and served by the backend. The codebase demonstrates strong patterns in modular route registration, plugin-style model registries, and streaming response handling, but also carries significant technical debt from heavy vendoring, duplicated code across third-party integrations, and version-sensitive patches to upstream libraries like vLLM.