A *dedicated public endpoint* is a public endpoint for online inference. It
offers the following benefits:

- **Dedicated networking**: When you send an inference request to a dedicated public endpoint, it is isolated from other users' traffic.
- **Optimized network latency**
- **Larger payload support**: Up to 10 MB.
- **Longer request timeouts**: Configurable up to 1 hour.
- **Generative AI-ready**: Streaming and gRPC are supported. Inference timeout is configurable up to 1 hour.

For these reasons, dedicated public endpoints are recommended as a best
practice for serving Gemini Enterprise Agent Platform online inferences.

> [!NOTE]
> **Note:** Tuned Gemini models can only be deployed to shared public endpoints.

To learn more, see
[Choose an endpoint type](https://docs.cloud.google.com/gemini-enterprise-agent-platform/machine-learning/predictions/choose-endpoint-type.md.txt).

## Create a dedicated public endpoint and deploy a model to it

You can create a dedicated endpoint and deploy a model to it by using the
Google Cloud console. For details, see
[Deploy a model by using the Google Cloud console](https://docs.cloud.google.com/gemini-enterprise-agent-platform/machine-learning/predictions/deploy-model-console.md.txt).

You can also create a dedicated public endpoint and deploy a model to it by
using the Gemini Enterprise API as follows:

1. [Create a dedicated public endpoint](https://docs.cloud.google.com/gemini-enterprise-agent-platform/machine-learning/predictions/create-public-endpoint.md.txt). Configuration of the inference timeout and request-response logging settings is supported at the time of endpoint creation.
2. [Deploy the model by using the Gemini Enterprise API](https://docs.cloud.google.com/gemini-enterprise-agent-platform/machine-learning/predictions/deploy-model-api.md.txt).

## Get online inferences from a dedicated public endpoint

Dedicated endpoints support both HTTP and gRPC communication protocols. For gRPC
requests, the x-vertex-ai-endpoint-id header must be included for proper
endpoint identification. The following APIs are supported:

- Predict
- RawPredict
- StreamRawPredict
- Chat Completion (Gemini Enterprise Agent Platform Model Garden only)

You can send online inference requests to a dedicated public endpoint by using
the Agent Platform SDK for Python. For details, see
[Send an online inference request to a dedicated public endpoint](https://docs.cloud.google.com/gemini-enterprise-agent-platform/machine-learning/predictions/get-online-predictions.md.txt#inference-request-dedicated).

## Tutorial

> [!NOTE]
> To learn more,
> run the " Model Garden - Gemma (Deployment)" notebook in one of the following
> environments:
>
> [![](https://docs.cloud.google.com/static/vertex-ai/images/colab-logo-32px.png)Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_gemma_deployment_on_vertex.ipynb)
>
>
> \|
>
> [![](https://docs.cloud.google.com/static/vertex-ai/images/colab-enterprise-logo-32px.png)Open in Colab Enterprise](https://console.cloud.google.com/agent-platform/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fcommunity%2Fmodel_garden%2Fmodel_garden_gemma_deployment_on_vertex.ipynb)
>
>
> \|
>
> [![](https://docs.cloud.google.com/static/vertex-ai/images/vertex-ai-workbench-logo-32px.png)Open
> in Agent Platform Workbench](https://console.cloud.google.com/agent-platform/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/community/model_garden/model_garden_gemma_deployment_on_vertex.ipynb)
>
>
> \|
>
> [![](https://docs.cloud.google.com/static/vertex-ai/images/github-logo-32px.png)View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_gemma_deployment_on_vertex.ipynb)

## Limitations

- Deployment of tuned Gemini models isn't supported.
- VPC Service Controls isn't supported. Use a Private Service Connect endpoint instead.

## What's next

- Learn about Gemini Enterprise Agent Platform online inference [endpoint types](https://docs.cloud.google.com/gemini-enterprise-agent-platform/machine-learning/predictions/choose-endpoint-type.md.txt).