Xorbits Inference is a model serving framework that lets you run open-source language, speech, and multimodal models through a unified inference API compatible with OpenAI's interface.
The tool solves the problem of managing multiple inference backends and APIs by providing a single abstraction layer. Instead of rewriting code when switching between different models or inference engines, you change a single line to swap implementations. Xinference handles deployment across cloud, on-premises, or local environments, supporting various backends including vLLM, llama.cpp, and other inference engines. It exposes a production-ready API that mimics OpenAI's interface, making it straightforward to integrate into existing applications.
Teams should adopt this tool if they need flexibility in model selection without code refactoring, want to avoid vendor lock-in to a single inference provider, or need to serve multiple model types—language models, speech recognition, and multimodal models—through a consistent interface. It suits projects ranging from local development on laptops to large-scale on-premises deployments. The tool is particularly valuable when you anticipate switching between open-source models or need to support multiple inference backends simultaneously.
The project maintains active engagement with its community through Discord and Telegram channels. Development shows consistent attention to expanding model support, with built-in support for numerous open-source models across different families. The codebase demonstrates ongoing refinement of the inference API and backend integrations, indicating sustained effort to keep pace with evolving model architectures and inference optimization techniques.
