Kserve
Kubernetes-based platform for deploying and serving AI/ML models at scale.
The open-source standard for serving AI models on Kubernetes; powerful and free, but it assumes real Kubernetes/MLOps capability.
An open-source, Kubernetes-native platform for serving and scaling ML and generative-AI model inference, abstracting away autoscaling, networking and rollouts.
It is becoming the open standard for model serving on Kubernetes (CNCF incubating): one declarative InferenceService gives you autoscaling (including scale-to-zero), canary rollouts, monitoring and pluggable runtimes like vLLM and TorchServe across many frameworks. The catch is that it lives on Kubernetes, so you need cluster/DevOps expertise and pay only for your own infrastructure.
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Alternatives
A managed inference platform (e.g. SageMaker, Vertex AI, Baseten) if you want no-ops serving.
vLLM or BentoML alone for simpler, single-node model serving.
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