KServe vs. Seldon Core
| Product | Rating | Most Used By | Product Summary | Starting Price |
|---|---|---|---|---|
 KServe | N/A | N/A | KServe is open-source AI Model Serving & Inference software for Kubernetes. Operators declare an InferenceService (and optional InferenceGraph) as custom resources. KServe then loads trained models from object storage or Hugging Face, starts a pluggable serving runtime, and exposes prediction or token APIs. It is a control plane for serving, not a training platform and not a hosted model catalog. | N/A |
 Seldon Core | N/A | N/A | Seldon Core is a Kubernetes-native AI Model Serving & Inference runtime. It loads trained machine learning (ML) and large language model (LLM) weights onto inference servers, exposes REST and gRPC endpoints, and executes those models in production so applications can obtain predictions or generated tokens at scale. The current architecture (Core 2) is bring-your-own-weights serving software that the operator runs on a cluster; it is not a hosted model-lab API and not a training platform. | N/A |
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| Editions & Modules | No answers on this topic | No answers on this topic | ||||||||||||||
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| Entry-level Setup Fee | No setup fee | No setup fee | ||||||||||||||
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