Accessing Multiple AI Models With the OpenRouter API: Getting Started & Using Intelligent Routing @realpython
Accessing Multiple AI Models With the OpenRouter API: Getting Started & Using Intelligent Routing  @realpython
Uploaded June 2026 | Updated September 2026, 2 weeks ago
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This is a preview of the video course, "Accessing Multiple AI Models With the OpenRouter API". One of the quickest ways to call multiple AI models from a single Python script is to use OpenRouter’s API, which acts as a unified routing layer between your code and multiple AI providers. By the end of this course, you’ll be able to access models from several providers through one unified API.

This convenience matters because the AI ecosystem is highly fragmented: each provider exposes its own API, authentication scheme, rate limits, and model lineup. Working with multiple providers often requires additional setup and integration effort, especially when you want to experiment with different models, compare outputs, or evaluate trade-offs for a specific task.

OpenRouter gives you access to thousands of models from leading providers like OpenAI, Anthropic, Mistral, Google, and Meta. You can switch between them without changing your application code.

This is a portion of the complete course, which you can find here: realpython.com/courses/multiple-ai-models-openrouter-api

And the original text tutorial is here: realpython.com/openrouter-api

The rest of the course covers:
- Modifying Routing Behavior
- Exercise: Build an OpenRouter Request Payload
- Implementing Model Fallbacks
- Weighing Your Options for Model Selection
- Exercise: Build a Fallback Models Payload
- Accessing Multiple AI Models With the OpenRouter API (Quiz)


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Accessing Multiple AI Models With the OpenRouter API: Getting Started & Using Intelligent Routing

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