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AI model serving and deployment tools

14 inference engines and platforms for serving models in production. Inference engines and orchestration tools for running models behind an API on your own or cloud GPUs. Compare throughput features, hardware support and Kubernetes integration.

How to read this page. The tools are grouped by category and are not ranked. Pricing labels come from vendors' own pages when we could confirm them. Always verify plans and limits on the vendor's site.

Chatbots & Assistants (1)

ToolWhat it doesPricingLink
OllamaRuns open language models locally through a command line and local API.See siteOfficial site

LLM APIs & Model Providers (4)

ToolWhat it doesPricingLink
LocalAIOpen-source, OpenAI-compatible API for running models locally.FreeOfficial site
MLC LLMUniversal LLM deployment engine for running models on many devices.FreeOfficial site
ModalServerless cloud for running AI workloads and model inference.FreemiumOfficial site
TensorRT-LLMNVIDIA open library for high-performance large language model inference.FreeOfficial site

AI Developer Tools (9)

ToolWhat it doesPricingLink
BentoMLOpen-source framework and cloud for packaging and serving AI models.See siteOfficial site
dstackOpen-source orchestration for AI training and inference across clouds.See siteOfficial site
KServeOpen-source model serving on Kubernetes.FreeOfficial site
llama.cppOpen-source C/C++ library for running language models efficiently on local hardware.FreeOfficial site
NVIDIA Dynamo-TritonNVIDIA open-source inference serving software (formerly Triton Inference Server) for deploying AI models at scale.See siteOfficial site
RayOpen-source framework for scaling Python and AI workloads.FreeOfficial site
SGLangOpen-source fast serving framework for large language and vision-language models.FreeOfficial site
SkyPilotOpen-source framework for running AI workloads on any cloud or Kubernetes.See siteOfficial site
vLLMOpen-source high-throughput inference engine for large language models.FreeOfficial site

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