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Abimael Martell ca7994d686 Revert "docs(site): add hero language playground"
This reverts commit 16df5fcf07.
2026-07-16 22:52:42 -07:00
Abimael Martell 16df5fcf07 docs(site): add hero language playground 2026-07-16 22:34:17 -07:00
Abimael Martell 14fb1a9296 docs(site): feature rust core in hero 2026-07-16 21:45:07 -07:00
Abimael Martell dcb143eee3 docs(site): keep hero install command inline 2026-07-16 21:41:30 -07:00
Abimael Martell d2b9b6559a docs(site): remove hero terminal scrollbar 2026-07-16 21:38:31 -07:00
Abimael Martell 5262c5fb6a docs(site): align footer wordmark 2026-07-16 21:35:05 -07:00
Abimael Martell 06724435a0 docs(site): emphasize package registries 2026-07-16 18:08:25 -07:00
Abimael Martell d17bba0780 docs(site): lead with node and cli 2026-07-16 18:01:51 -07:00
Abimael Martell 9fc674c127 docs(site): redesign open-source project page 2026-07-16 17:54:11 -07:00
Abimael Martell a910b7df1d docs(benchmark): refresh parser comparison (#178)
* docs: refresh benchmark comparison

* docs(site): refresh benchmark section

* docs: reframe benchmark positioning

* docs: focus benchmark positioning on best fit
2026-07-16 17:43:53 -07:00
6 changed files with 715 additions and 381 deletions
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@@ -23,20 +23,21 @@ Built by [Firecrawl](https://firecrawl.dev) to handle text-based PDFs locally in
## Benchmark
Evaluated on the [opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs). Only direct text extraction engines are shown — no OCR, no ML models. Scores are 0-1, higher is better.
Evaluated on the [opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs). Only local engines without model-based PDF parsing are shown; OCR was disabled. Scores are 0-1, higher is better.
| Engine | Overall | Reading Order (NID) | Tables (TEDS) | Headings (MHS) | Speed (200 docs) |
|---|---|---|---|---|---|
| pdf-inspector | **0.875** | **0.915** | **0.814** | 0.788 | 3.3s |
| opendataloader | 0.831 | 0.902 | 0.489 | 0.739 | 3.0s |
| pymupdf4llm | 0.73 | 0.89 | 0.40 | 0.41 | 18s |
| markitdown | 0.59 | 0.84 | 0.27 | 0.00 | 23s |
| 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 |
For context, engines that use OCR/ML (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 any OCR, in 3.3 seconds.
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.
**Where we do well:** The best overall, reading-order, and table scores among the direct extraction engines shown.
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.
**Where we lag:** Some direct engines remain slightly faster, and OCR-based engines can recover text that has no usable PDF text layer.
**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.
Use the [paired benchmark harness](docs/benchmarking.md) to compare two local builds against the exact same corpus and evaluator revision.
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@@ -28,6 +28,14 @@ The OpenDataLoader repository is external and keeps its normal
temporary directory before evaluating it, so the baseline and candidate cannot
overwrite one another.
## Published comparison protocol
The public benchmark table was refreshed on July 16, 2026, on an Apple M4 Pro
using pdf-inspector 0.1.6, LiteParse 2.6.0, OpenDataLoader 2.1.1,
PyMuPDF4LLM 0.2.0, and MarkItDown 0.1.4. Every engine processed the same 200
PDFs with OCR disabled. Reported speed is the median of three complete corpus
runs; quality scores come from the benchmark evaluator over all 200 outputs.
## Optional backend evidence probe
The evidence probe compares positioned `pdf2md` items with MuPDF structured
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@@ -14,15 +14,17 @@ Built by [Firecrawl](https://firecrawl.dev) to handle text-based PDFs locally in
## Benchmark
[opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs), direct-extraction engines only — no OCR, no ML. Scores 01, higher is better:
[opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs), local engines without model-based PDF parsing; OCR disabled. Scores 01, higher is better:
| Engine | Overall | Reading order | Tables (TEDS) | Headings | Speed |
|---|---|---|---|---|---|
| **pdf-inspector** | **0.875** | **0.915** | **0.814** | 0.788 | 3.3s |
| opendataloader | 0.831 | 0.902 | 0.489 | 0.739 | 3.0s |
| pymupdf4llm | 0.73 | 0.89 | 0.40 | 0.41 | 18s |
| **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 |
OCR/ML engines (docling, marker, mineru) score 0.830.88 overall but take 2180 minutes on the same corpus. Full numbers in the [repo README](https://github.com/firecrawl/pdf-inspector#benchmark).
Refreshed July 16, 2026, on Apple M4 Pro; speed is the median of three complete corpus runs. Full methodology and versions are in the [repo README](https://github.com/firecrawl/pdf-inspector#benchmark).
## Install
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@@ -14,15 +14,17 @@ Built by [Firecrawl](https://firecrawl.dev) to handle text-based PDFs locally in
## Benchmark
[opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs), direct-extraction engines only — no OCR, no ML. Scores 01, higher is better:
[opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs), local engines without model-based PDF parsing; OCR disabled. Scores 01, higher is better:
| Engine | Overall | Reading order | Tables (TEDS) | Headings | Speed |
|---|---|---|---|---|---|
| **pdf-inspector** | **0.875** | **0.915** | **0.814** | 0.788 | 3.3s |
| opendataloader | 0.831 | 0.902 | 0.489 | 0.739 | 3.0s |
| pymupdf4llm | 0.73 | 0.89 | 0.40 | 0.41 | 18s |
| **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 |
OCR/ML engines (docling, marker, mineru) score 0.830.88 overall but take 2180 minutes on the same corpus. Full numbers in the [repo README](https://github.com/firecrawl/pdf-inspector#benchmark).
Refreshed July 16, 2026, on Apple M4 Pro; speed is the median of three complete corpus runs. Full methodology and versions are in the [repo README](https://github.com/firecrawl/pdf-inspector#benchmark).
## Install
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@@ -14,15 +14,17 @@ Built by [Firecrawl](https://firecrawl.dev) for hybrid OCR pipelines — extract
## Benchmark
[opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs), direct-extraction engines only — no OCR, no ML. Scores 01, higher is better:
[opendataloader-bench](https://github.com/opendataloader-project/opendataloader-bench) corpus (200 PDFs), local engines without model-based PDF parsing; OCR disabled. Scores 01, higher is better:
| Engine | Overall | Reading order | Tables (TEDS) | Headings | Speed |
|---|---|---|---|---|---|
| **pdf-inspector** | 0.83 | 0.88 | **0.66** | 0.74 | **4s** |
| opendataloader | 0.84 | 0.91 | 0.49 | 0.74 | 11s |
| pymupdf4llm | 0.73 | 0.89 | 0.40 | 0.41 | 18s |
| **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 |
OCR/ML engines (docling, marker, mineru) score 0.830.88 overall but take 2180 minutes on the same corpus. Full numbers in the [repo README](https://github.com/firecrawl/pdf-inspector#benchmark).
Refreshed July 16, 2026, on Apple M4 Pro; speed is the median of three complete corpus runs. Full methodology and versions are in the [repo README](https://github.com/firecrawl/pdf-inspector#benchmark).
## Install
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