kserve
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes
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Decision brief
Good fit when
- When you need a standardized and scalable way to deploy generative and predictive models across multiple frameworks.
- If your existing infrastructure is built around Kubernetes, as kserve/kserve is tightly integrated with it for efficient deployment.
Avoid when
- When your team or organization lacks expertise in Kubernetes, as effective use of kserve/kserve requires familiarity with Kubernetes operations.
- If the deployment environment is not compatible with Kubernetes. KServe's architecture relies on the Kubernetes ecosystem for orchestrating model deployments.
- Requirements:
- Requires Docker; Requires a Kubernetes cluster to run.
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of today
- Provenance
- Not a fork · Organization account
- As of today
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
go get github.com/kserve/kserveSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
kserve/kserve provides a scalable inference platform for deploying generative and predictive models across multiple frameworks using Kubernetes.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 24, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 24, 2026
- Languages
- go
Source: github.language · Aug 24, 2026
Categories
Tags
README
:hammer_and_wrench: Installation
Standalone Installation
- Standard Kubernetes Installation: Compared to Serverless Installation, this is a more lightweight installation. However, this option does not support canary deployment and request based autoscaling with scale-to-zero.
- Knative Installation: KServe by default installs Knative for serverless deployment for InferenceService.
- ModelMesh Installation: You can optionally install ModelMesh to enable high-scale, high-density and frequently-changing model serving use cases.
- Quick Installation: Install KServe on your local machine.
Kubeflow Installation
KServe is an important addon component of Kubeflow, please learn more from the Kubeflow KServe documentation. Check out the following guides for running on AWS or on OpenShift Container Platform.
For agents
This page has a .md twin and JSON over the API.