Benchmarks are becoming the core competency of any company.
Our company mission is to build the world’s best models for document processing. This also means that we have to build the world’s best benchmarks for doc parsing and extraction.
It’s been incredible to see the adoption of ParseBench the past few months. We have 26k+ monthly downloads on Hugging Face, 147+ models benchmarked, and has been cited by other labs in the space (Cohere, Mistral, etc.).
We use this as a benchmark to push our own internal capabilities within LlamaParse, and also to track the advancement of recent frontier/open-weight models (most recently, Gemini 4 Argon and Muse Spark/Wonder).
We’re happy to help apply this to any company looking at evaluating document processing solutions. Even if you don’t use our docs, you may find our metrics for evaluating various dimensions (e.g. tables, reading order, layout) useful.
Check out ParseBench: https://www.parsebench.ai/
Hugging Face: https://huggingface.co/datasets/llamaindex/ParseBench