Inferencing made better.
Run any model
with total control

Universal compatibility Run any model, any GPU, anywhere

Enterprise security Scale with confidence using SOC2 compliant VPC deployments and RBAC

Maximum performance Deploy faster and at a fraction of the cost with our inference optimization engine

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Xinference Platform Demo

Universal, enterprise
grade inference

Effortlessly deploy any or your own models with one command. Whether you are a researcher, developer, or data scientist, Xinference empowers you to unleash the full potential of AI today.

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One-click deployment.
Complete control from day one.

bash

$ pip install xinference[all]

Simple setup

Simple one-command installation or Docker deployment
Works on your existing infrastructure—cloud, on-premise, or hybrid

OpenAI

Gemini

Claude

NVIDIA

AMD

Intel

Meta

HuggingFace Mistral AWS Azure DeepSeek

Maximum flexibility

Mix & match models to optimise workload, cost, or performance
300+ models available — Model Hub ↗
Supporting 20+ heterogeneous GPUs
Deploy on cloud, on-premise, or hybrid

🏛️SOC 2

🇪🇺EU GDPR

⚕️HIPAA

Enterprise grade security

Fine-grained data policies for your organisation
SOC 2, GDPR & HIPAA compliant
Prompts only reach models you trust

Trusted by teams building at scale

See how teams optimise performance and cut costs with Xinference

40%

reduction in AI infrastructure costs

DataCore →

5×

faster model inference for production workloads

NeuralSoft →

👤

"Xinference aligned with our vision: to iterate faster, scale smarter, and operate more efficiently across all our AI workloads."

Sarah Chen

Head of AI Platform

CloudScale →

👤

"We chose Xinference not just for what we needed today, but for where we know we're heading. As our AI workloads grow more complex, Xinference gives us the infrastructure to scale without limits."

James Park

Engineering Lead, AI Infrastructure

QuantumAI →

99%

uptime SLA across enterprise deployments

Infratech →

10×

faster model deployment vs. previous solution

Synapse Labs →

3×

increase in model throughput after migration

VectorEdge →

$2M+

annual GPU cost savings across 12 deployments

Orbis AI →

👤

"Switching to Xinference cut our time-to-deploy from days to minutes. The team finally has the breathing room to focus on model quality instead of infrastructure."

Priya Nair

VP of Machine Learning

DeepLayer →

Customers using Xinference →