lm-evaluation-harness

The lm-evaluation-harness is an open-source benchmarking framework maintained by EleutherAI. It runs language models against hundreds of standardized academic tasks through one interface, which is how many leaderboards and research papers produce comparable numbers. The harness backs Hugging Face's Open LLM Leaderboard and accepts models from Transformers, vLLM, commercial APIs, and other backends, so the same test suite applies across very different deployments. Researchers cite it widely for reproducible numbers, and it underpins leaderboards comparing open and commercial models on equal footing. Custom task definitions let teams add domain benchmarks that run through the same interface.

Key Capabilities:

• Hundreds of standardized benchmark tasks in one framework

• Model support for Transformers, vLLM, and commercial APIs

• Reproducible few-shot and zero-shot evaluation configs

• Custom task definitions for domain-specific benchmarks

• Consistent metrics for cross-model comparison

• MIT license powering widely cited leaderboards