Too many AI models? OpenRouter's Ori Eval picks the right one for your app

AI model aggregator OpenRouter has launched Ori Eval, a tool that helps developers figure out which model their app should actually be using. It scans your codebase, finds every place you call a model, and then runs multiple candidate models against real tasks from your project.

You can tell it whether you primarily care about quality, speed, or cost. During evaluation, Ori Eval locks down the test framework, model configuration, and reasoning effort, then hands back a direct ranking — so models are actually compared under the same conditions.

It doesn't just grade answers, either. It also checks whether an agent called the right tools and avoided actions it shouldn't take. Describe a bug in plain English, and Ori Eval will generate a test that reproduces it. After you fix it, hook it into GitHub Actions and future model swaps, prompt changes, or code edits will automatically check whether the problem has crept back.

Public leaderboards can compare general abilities, but they can't tell you which model is right for a customer service bot, a search product, or a coding tool. Ori Eval turns manual trial-and-error into an automated selection process grounded in your actual business logic.