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Batch Inference is now generally available on Runpod Serverless

MODEL HUB

Model Hub

Call a model by API, or serve open weights on your own endpoint. Every page lists the GPU, the code, and the price.

EVERY MODALITY

Language, vision, image, video and audio models. Each page has the code to call it and a deploy link.

43 PUBLIC ENDPOINTS

Call 43 models by API with no setup. Open weights run on your own Serverless endpoint or Pod.

models

How should I deploy an AI model?

Use Public Endpoints for API access to pre-deployed models. Choose Serverless for your own inference endpoint, Pods for control of a dedicated environment, or Clusters for workloads that span multiple nodes.

Compare Public Endpoints, Serverless, Pods, and Clusters
Deployment optionChoose it whenSetup and controlScalingHow billing works
Public EndpointsCall a supported, pre-deployed model through an API.Use a Runpod API key. Runpod hosts the model.Runpod manages the model infrastructure.Usage-based rates vary by model and output type.
ServerlessServe your own model behind an endpoint.Deploy a worker image and configure your endpoint.Flex workers can scale to zero; active workers stay running.Compute is billed per second while workers run, including startup and idle timeout. Storage is separate.
PodsUse a custom serving stack, fine-tune, or run persistent workloads.Configure a dedicated environment and manage the software.Manage your Pod resources directly.Compute is billed per second while the Pod runs. Retained storage can still incur charges.
ClustersRun distributed training or inference across multiple nodes.Configure your workload on a managed multi-node cluster.Choose the node configuration for your workload.Rates depend on GPU type and node count. See current pricing in the linked documentation.

Deployment options vary by model. Check the model page for supported routes, then follow the linked documentation for setup and billing details.

Deploy any open model from Hugging Face

Runpod Serverless serves open models with vLLM. Pick one of these 314 for a page with one-click deploy, or paste any Hugging Face model ID when you create an endpoint.

Questions about running open models on Runpod

What models can I run on Runpod?

Any open model that vLLM supports can run on Runpod Serverless. The hub lists the ones with their own page, each with the GPU to start on and a deploy link. For anything else, paste the Hugging Face model ID when you create a Serverless endpoint.

Should I use a Public Endpoint or Serverless?

Use a Public Endpoint to call a pre-deployed model through the Runpod API with no setup. Use Serverless to serve your own endpoint, Pods for a dedicated environment, or Clusters for workloads that span multiple nodes.

How much does it cost to run an open model?

Public Endpoints bill at rates set by model and output type. Serverless and Pods bill per second of compute, and each model page shows the starting GPU. Check the model page and the pricing page for current rates.

Build what’s next.

Build, train, and scale AI workloads on Runpod with cloud GPUs, Serverless, and Clusters.

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More models in the directory

Community models with their own pages that the lists above do not show.

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