KServe
A Kubernetes-native platform for serving predictive and generative AI models at scale.
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About KServe
KServe runs on a Kubernetes cluster and provides a standard way to deploy and scale machine learning models for inference. It covers both classic predictive models and generative AI models, and works with multiple model frameworks.
The project ships Helm charts, install scripts and a Python component. It suits platform teams that already run Kubernetes and want a shared, standardized model serving layer.
Strengths
- Standard model serving layer on Kubernetes
- Handles predictive and generative models
- Supports multiple model frameworks
- Helm charts included for installation
Limitations
- Requires a Kubernetes cluster and the skills to run one
- Not suited to single-machine or hobby use
Details
- Pricing
- FreeFree and open source.
- License
- Open source, license not stated
- Developer
- The KServe contributors
- Platforms
- Self-hosted
- How it runs
- Self-hosted
- Account
- Not required
- Best suited for
- Platform teams serving AI models on Kubernetes
- Categories
- Container tools, AI developer tools
- Last verified
- Added
- Sources
Alternatives to KServe
Compare allSoftware that can replace KServe for an important use case, and what changes if you switch.
NVIDIA Triton Inference Server
An open-source inference server for deploying machine learning models from many frameworks on GPUs and CPUs.
NVIDIA Triton Inference Server serves models from many frameworks on GPUs and CPUs with Docker-based deployment, without depending on Kubernetes.
GPUStack
An open-source GPU cluster manager for serving AI models with vLLM and SGLang on your own hardware.
GPUStack pools GPUs across machines to serve models with vLLM and SGLang, and deploys with Docker Compose or Kubernetes Helm.
OpenVINO Model Server
A self-hosted inference server for serving AI models that have been optimized with OpenVINO.
OpenVINO Model Server serves models at scale from container images, but requires models in or converted to OpenVINO-supported formats.
Kubeflow
A Kubernetes-native set of open-source projects for running data, ML and AI workloads.
Kubeflow is a broader Apache-2.0 set of Kubernetes projects for training and serving ML workloads, adopted modularly and backed as a graduated CNCF project.
Similar software
Related functionality, not necessarily a direct replacement.
vLLM
High-throughput, memory-efficient inference and serving engine for LLMs.
SGLang
A serving framework for running large language models and multimodal models on your own GPUs.
ZenML
An open-source framework for writing ML pipelines and AI agents in Python and running them on your own infrastructure.
Flyte
An open-source orchestration platform for durable data, machine learning and AI agent workflows written in Python.
Xinference
An open-source inference server for running language, speech and multimodal models through one API.
