Get started

In this guide, you will learn how to create your first AI Gateway. You can create multiple gateways to control different applications.

Prerequisites

Before you get started, you need a Cloudflare account.

Sign up

Create gateway

Then, create a new AI Gateway.

Dashboard

To set up an AI Gateway in the dashboard:

1. Log into the Cloudflare dashboard ↗ and select your account.
2. Go to AI > AI Gateway.
3. Select Create Gateway.
4. Enter your Gateway name. Note: Gateway name has a 64 character limit.
5. Select Create.

API

To set up an AI Gateway using the API:

1. Create an API token with the following permissions:

   • AI Gateway - Read
   • AI Gateway - Edit

2. Get your Account ID.

3. Using that API token and Account ID, send a POST request to the Cloudflare API.

Connect application

Next, connect your AI provider to your gateway.

AI Gateway offers multiple endpoints for each Gateway you create - one endpoint per provider, and one Universal Endpoint.

Supported providers

• Amazon Bedrock
• Anthropic
• Azure OpenAI
• Cohere
• Google AI Studio
• Google Vertex AI
• Groq
• HuggingFace
• Mistral AI
• OpenAI
• Perplexity
• Replicate
• Universal Endpoint
• Workers AI

If you do not have a provider preference, start with one of our dedicated tutorials.

Onboarding tutorials

• OpenAI
• Worker AI

View analytics

Now that your provider is connected to the AI Gateway, you can view analytics for requests going through your gateway.

Your AI Gateway dashboard shows metrics on requests, tokens, caching, errors, and cost. You can filter these metrics by time and provider-type.

To view analytics in the dashboard:

1. Log into the Cloudflare dashboard ↗ and select your account.
2. Go to AI > AI Gateway.
3. Make sure you have your gateway selected.

Note

The cost metric is an estimation based on the number of tokens sent and received in requests. While this metric can help you monitor and predict cost trends, refer to your provider’s dashboard for the most accurate cost details.

Next steps

• Learn more about caching for faster requests and cost savings and rate limiting to control how your application scales.
• Explore how to specify model or provider fallbacks for resiliency.
• Learn how to use low-cost, open source models on Workers AI - our AI inference service.