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docs(readme): refresh local parser benchmark results (#192)

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* docs(readme): refresh parser benchmark results

* docs(readme): include stored parser results

* docs(readme): refresh remaining parser results

* docs: sync benchmark references
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Abimael Martell
2026-07-31 22:58:46 -06:00
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@@ -28,17 +28,17 @@ Evaluated on the [opendataloader-bench](https://github.com/opendataloader-projec
| Engine | Overall | Reading Order (NID) | Tables (TEDS) | Headings (MHS) | Speed (200 docs) |
|---|---|---|---|---|---|
| pdf-inspector | **0.875** | **0.915** | **0.814** | 0.788 | **2.8s** |
| liteparse | 0.870 | 0.908 | 0.693 | **0.811** | 13.9s |
| opendataloader | 0.843 | 0.912 | 0.489 | 0.760 | 9.8s |
| pymupdf4llm | 0.735 | 0.886 | 0.401 | 0.424 | 15.5s |
| markitdown | 0.583 | 0.879 | 0.000 | 0.000 | 6.7s |
| pdf-inspector | **0.875** | **0.915** | **0.814** | 0.788 | **0.470s** |
| liteparse | 0.873 | 0.913 | 0.693 | **0.811** | 0.750s |
| opendataloader | 0.831 | 0.902 | 0.489 | 0.739 | 2.569s |
| pymupdf4llm | 0.735 | 0.886 | 0.401 | 0.424 | 17.117s |
| markitdown | 0.589 | 0.844 | 0.273 | 0.000 | 16.165s |
Results were refreshed on July 16, 2026, on an Apple M4 Pro. Engine versions were pdf-inspector 0.1.6, LiteParse 2.6.0, OpenDataLoader 2.1.1, PyMuPDF4LLM 0.2.0, and MarkItDown 0.1.4. Speed is the median of three complete corpus runs.
Results were refreshed on July 31, 2026, on an Apple M4 Pro. Engine versions were pdf-inspector 0.2.6, LiteParse 2.10.1, OpenDataLoader 2.2.1, PyMuPDF4LLM 0.2.0, and MarkItDown 0.1.5. Speed is the median of five alternating or rotating complete corpus runs after an excluded warm-up run, with each parser processing documents sequentially in a single process.
For context, engines that use OCR or model-based document parsing (docling, marker, mineru) score 0.83-0.88 overall but take 2-180 minutes on the same corpus — pdf-inspector reaches the top of that range without either, in 2.8 seconds.
The complete parser configuration, per-document predictions, evaluator output, and generated charts are available in the [reproducible results branch](https://github.com/firecrawl/opendataloader-bench/tree/abi/pdf-parser-benchmark-results).
**Best fit:** Native-text PDFs where speed, reading order, and table structure matter. pdf-inspector delivered the highest overall, reading-order, and table scores, along with the fastest complete run in this benchmark. That makes it a strong local default for reports, research papers, financial documents, invoices, and legal PDFs that need clean, structured Markdown without adding OCR latency or infrastructure.
**Best fit:** Native-text PDFs where speed, reading order, and table structure matter. In this comparison, pdf-inspector delivered the higher overall, reading-order, and table scores, along with the fastest complete run. That makes it a strong local default for reports, research papers, financial documents, invoices, and legal PDFs that need clean, structured Markdown without adding OCR latency or infrastructure.
Use the [paired benchmark harness](docs/benchmarking.md) to compare two local builds against the exact same corpus and evaluator revision.