Xinference
Xinference: A flexible serving stack for open models across private and cloud environments. Ranked #18 of 25 in AI Model Hosting by our editors (7.4/10); pricing: Free plan; best for open-model serving across private and cloud environments.
At a glance
- Editor score7.4 / 10
- PricingFree plan
- Best forOpen-model serving across private and cloud environments
- Free planYes
- Paid fromFree
- Deployment modeBoth
- Facts checked23 Sep 2026
Where it wins
- Serves language, embedding, speech, and image-generation models
- OpenAI-compatible REST API supports streaming and model routing
- Offers GPU pooling, autoscaling, monitoring, and private deployment
Where it doesn't
- Integrations listed are limited to LangChain, LlamaIndex, and Dify
- Model API and dedicated GPU deployment rates require contacting sales
- Community edition offers single-cluster scaling and GitHub community support
Our verdict on Xinference
Xinference provides an inference platform for serving open language, embedding, speech, and multimodal models through an OpenAI-compatible API. It is aimed at teams that want to run open models locally, in a private environment, or through managed cloud deployments. A Community edition supports self-hosting, while commercial options include a per-token Model API, dedicated GPU instances, and private deployment on a customer cloud, data centre, or offline environment.
The platform covers multiple inference workloads rather than language models alone: it can serve embedding, transcription, text-to-speech, and image-generation models alongside language models. Its API supports streaming, and request routing can span models and infrastructure. GPU pooling and autoscaling address deployment capacity, while request logs and TTFT/TPOT metrics provide operational visibility. Running a local server through the command line, Web UI, or Python client gives teams several ways to work with a deployment. Listed integrations are LangChain, LlamaIndex, and Dify, so teams with other ecosystem requirements should check fit before choosing it.
The Community plan is an Apache-2.0 inference engine with single-cluster scaling, NVIDIA hardware validation, and GitHub community support. Commercial offerings include Model API billing per token and per model, managed dedicated GPU instances, private deployment, and a Xinference plus Xagent bundle hosted in Australia. The published information does not give rates for Model API or dedicated GPU deployments, so those options require a sales conversation. Enterprise options add multi-cluster scaling, failover, and named support. Xinference suits teams prioritizing open-model breadth and control over deployment location; teams seeking a tightly specified public price or a broad set of listed integrations may prefer to compare alternatives.
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Xinference pricing
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Xinference fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Deployment mode | Both |
| Autoscaling | Yes |
| GPU accelerators | Yes |
| Private deployment | Yes |
| Supported model formats | Not verified |
| Batch inference | Yes |
| Deployment regions | Not verified |
| Deployment | Cloud, Self-hosted, Browser extension |
| Platforms | Web, Linux |
| Compliance & security | SSO/SAML |
| Support | Community, Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 3 integrations: LangChain, LlamaIndex, Dify |
| Pricing | Free plan (source) |
| Website | xinference.co |
| Facts checked | 23 Sep 2026 |
Xinference integrations
Xinference lists 3 integrations on its own site.
- LangChain
- LlamaIndex
- Dify
Alternatives to Xinference
- BasetenManaged model APIs with GPU deployments, autoscaling, training, and observability.9.4
- BentoMLBentoML gives open-source teams flexible paths from local serving to managed inference.9.2
- KServeOpen-source model serving for teams operating extensible inference on Kubernetes.9.1
See all Xinference alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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