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ParseBench reportedly gets 26,000-plus monthly Hugging Face downloads

A team member says 147-plus models have been benchmarked, with ParseBench also used to test LlamaParse.

Jerry LiuJL
1 Source, 2h ago, first seen 2h ago

TLDR

In October 2026, a ParseBench team member said the document-parsing benchmark had 26,000-plus monthly downloads on Hugging Face and had benchmarked 147-plus models. They said the team uses it to develop LlamaParse’s capabilities and track other models. Its evaluation metrics include tables, reading order and layout.

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1 Source, first seen 2h ago

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Combined views

1.6K

1 Source, first seen 2h ago

22 likes12 comments3 saves1 reposts
Image: @jerryjliu0 on X

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1 Source

Jerry Liu@jerryjliu0Benchmarks 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/ParseBench2h
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    1 Source

    Jerry Liu@jerryjliu0Benchmarks 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/ParseBench2h
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