Xinference

ML inferencexinference

Open-source serving platform for LLM, embedding, image and audio models, local or clustered.

Provider
default
Category
Compute
Also known as
Xorbits Inference
Properties · 3 set by this component
propertytypevaluesrequiredkind defaultthis component
acceleratorenumnone | gpu | asicnononeinherited
acceleratorModel · advancedenumnvidia-h100 | nvidia-h200 | nvidia-b200 | nvidia-l4 | nvidia-a100 | amd-mi300x | aws-trainium | aws-inferentia | google-tpu | intel-gaudi | groq-lpu | cerebras-wseno—inherited
deployment · component propertyenumlocal | clusternolocalinherited
embeddingSyncMinutes · advancedinteger—no—inherited
engine · component propertyenumvllm | sglang | llama-cpp | transformers | mlxno—inherited
inputsenumlive | historical | bothnolive▸ live
instancesinteger—no—inherited
managedboolean—nofalse▸ false
port · component propertyinteger—no9997inherited
snapshotToObjectStore · advancedboolean—nofalseinherited
trainingenumbatch | onlinenobatch▸ batch
Rules that apply · 1

Every rule whose selector covers this component's kind or its category. Whether a rule fires depends on the design: its properties, its edges and its groups.

stateful-node-without-zone-redundancy

A stateful compute node pinned to exactly one availability zone disappears with that zone, and its state goes with it. Nodes inside a cell are exempt, because there the cell is deliberately single-zone and redundancy comes from the other cells.

  • — all of these hold:
  • — the node's `stateless` is false
  • — the node sits inside exactly 1 availability-zone group
  • — this does not hold:
  • — the node sits inside at least one cell group
Use it in a design
nodes:
  - { id: "xinference", component: "xinference" }
Other ML inference products · 37
Source
# yaml-language-server: $schema=../../schema/component.schema.json
# Xinference (Xorbits Inference): open-source serving platform for LLM, embedding, image and audio models with
# OpenAI-compatible APIs. Per "Using Xinference", xinference-local listens on port 9997 and a cluster runs one
# supervisor with workers; each model is launched on a chosen engine (vLLM, SGLang, llama.cpp, Transformers or MLX).
schemaVersion: "1"
type: "component"
id: "xinference"
kind: "ml-inference"
provider: "default"
docs: "https://inference.readthedocs.io/en/latest/getting_started/using_xinference.html"
aliases: ["Xorbits Inference"]
defaults:
  training: "batch"
  inputs: "live"
  managed: false
properties:
  port:
    type: "integer"
    default: 9997
  deployment:
    type: "enum"
    values: ["local", "cluster"]
    default: "local"
  engine:
    type: "enum"
    values: ["vllm", "sglang", "llama-cpp", "transformers", "mlx"]

The same page as markdown, for an agent: /catalogue/components/xinference.md