simple-evals is a lightweight evaluation framework developed by OpenAI for quickly testing models against small, focused benchmarks. It is designed to help researchers and developers run targeted evaluations without the complexity of large-scale pipelines. By emphasizing simplicity, the framework makes it easy to define new tasks, run evaluations, and interpret results in a reproducible way. It is particularly useful for sanity checks, exploratory research, and comparing performance across different models or configurations. The project provides clear structures for defining datasets, metrics, and evaluation logic, while staying minimal enough to adapt for custom use cases. With its straightforward design, simple-evals is well-suited for rapid iteration and for teams that want to integrate evaluation into their model development workflows.
Features
- Lightweight framework for small, focused model evaluations
- Simple setup for defining datasets, tasks, and metrics
- Reproducible results with minimal configuration
- Useful for sanity checks and exploratory benchmarking
- Easy to extend with custom evaluation logic
- Supports comparing multiple models or configurations