Xinference (Xorbits Inference) is an open-source distributed inference platform abstracting away hardware complexity to run 600+ LLMs and multimodal models with a unified API. Deploy the same code on your laptop, on-premises cluster, or cloud infrastructure without modification. Xinference handles resource management, model quantization, batch scheduling, and hardware utilization. The platform supports NVIDIA GPUs, AMD GPUs (via HIP), Intel NPUs, Apple Metal, and CPU-only inference, democratizing model deployment across the ecosystem rather than locking users into proprietary frameworks.
Xinference emphasizes compatibility and ease of integration. RESTful APIs with OpenAI protocol compatibility allow drop-in replacement of commercial APIs. Swap a ChatGPT call for a local Qwen or DeepSeek call by changing one endpoint URL. The distributed design enables cross-device and cross-server deployment, so a single inference cluster can span multiple nodes with heterogeneous hardware. Inference optimization engines (vLLM, SGLang, LmDeploy) are bundled, and quantization support (AWQ, GPTQ, FP8) lets teams optimize for latency or throughput. Integration with LangChain, LlamaIndex, Dify, and Chatbox means existing orchestration workflows plug in seamlessly.
Teams building private AI deployments for regulatory compliance, data sovereignty, or cost control choose Xinference. MLOps teams managing multi-tenant inference or auto-scaling workloads benefit from its distributed scheduling and resource pooling. Helm chart support makes Kubernetes deployments straightforward. Active development adds model support monthly, and the community-driven roadmap reflects real deployment needs. For organizations avoiding vendor lock-in while needing production-grade inference infrastructure, Xinference provides a solid foundation.
