openai/frontier-evals

What it solves

Frontier Evals provides a standardized framework for measuring the capabilities of advanced AI models. It addresses the need for rigorous, reproducible testing across complex domains like software engineering, academic research, and smart contract security.

How it works

The repository acts as a collection of isolated evaluation projects. Each project contains its own environment configuration, dependencies, and documentation. Users navigate to a specific evaluation directory (such as PaperBench, SWE-Lancer, or EVMbench), synchronize the environment using uv, and follow the project-specific instructions to run tests and interpret model performance.

Who it’s for

This project is intended for AI researchers, developers, and engineers who need to benchmark frontier AI models against real-world, high-stakes tasks using standardized, reproducible methodologies.

Highlights

• Includes PaperBench for replicating state-of-the-art AI research papers.
• Features SWE-Lancer for testing model performance on real-world freelance software engineering tasks.
• Contains EVMbench for evaluating AI capabilities in smart contract security.
• Uses a modular, isolated directory structure to ensure dependencies and configurations remain consistent for each specific benchmark.