superPDF Performance
Free, no account, no upload: everything here runs in your browser, on your device. A 1 GB, 2,000-page PDF opens and edits in seconds, and superPDF’s own reader scores 59.5 on a ParseBench sample, instantly and with nothing to download.
Two ways superPDF reads a PDF
| Compared | superPDF reader (default) | High-accuracy reading for scans (optional) |
|---|
| Used for | Every PDF, automatically | Scanned pages, when you choose it |
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| Download | None | 871 MB, once |
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| Speed | Instant for digital PDFs; scans about 3 to 4 s a page | About 23 s a page |
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| Best at | Digital PDFs: exact text, tables and charts drawn in the PDF | Scans, other scripts (Russian, Korean, Hebrew), charts that are images, hard tables |
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| Words found on our 20-page scan | 67.9% | 81.7% |
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| Tables (ParseBench 78-PDF sample) | 62.9 | 75.4 |
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You don’t pick a reader: superPDF uses its own reader for every PDF, and offers high-accuracy reading only when a page is scanned. superPDF OCR is built on Tesseract, the open-source OCR engine.
Big files
1 GB, 2,000-page PDF (Chrome, Apple M4 Pro, 48 GB memory, 2026-10-11)
| Tool | Time | Peak memory |
|---|
| Redact PDF, 2 pages | About 10 s | 1.9 GB |
| Annotate PDF, 2 pages | About 10 s | 1.9 GB |
| Watermark PDF, chosen pages | About 8 s | 1.8 GB |
| Crop & resize, one page | About 9 s | 1.9 GB |
| Compare PDFs, two 2,000-page versions | About 72 s | 2.8 GB |
| PDF to text, Markdown, 2,000 text pages | 4.4 s | – |
Scanned pages
| Reader | Speed | Where |
|---|
| superPDF OCR (English) | 20 pages in 81 s, 50 pages in 142 s (3 to 4 s a page) | Every device, automatically |
| High-accuracy reading (LightOnOCR-3 0.8B) | About 23 s a page (11 to 50 s) | Computers, when you choose it; 871 MB download in about 25 s |
The page stays usable while it reads.
Words found on a 20-page mixed-language scan
| Reader | Words found |
|---|
| superPDF OCR | 67.9% |
| High-accuracy reading | 81.7% |
High-accuracy reading reads English, other European languages, Russian, Hebrew and Korean.
Accuracy
ParseBench (78-PDF sample, out of 100)
| Reader | Overall | Tables | Charts | Content | Formatting | Grounding |
|---|
| superPDF reader (default) | 59.5 | 62.9 | 60.4 | 80.5 | 52.0 | 41.9 |
| High-accuracy reading for scans (optional) | 59.7 | 75.4 | 50.5 | 79.8 | 44.1 | 48.5 |
Both readers turn charts drawn in the PDF into data tables; high-accuracy reading also reads charts that are pictures.
olmOCR-bench (42-PDF sample, 333 tests)
| Reader | Tests passed |
|---|
| High-accuracy reading for scans (optional) | 77.2% |
How we measured
- Machine: MacBook Pro, Apple M4 Pro, 48 GB of memory.
- Browser and dates: Chrome, October 11 and 12, 2026.
- Files: a 1 GB PDF of 2,000 scanned-style pages; a 2,000-page text-only report; a 20-page mixed-language scan.
- Benchmark samples: ParseBench (LlamaIndex), 78 PDFs, 20 per dimension, seed 7; olmOCR-bench (Ai2), 42 PDFs, 333 tests.
- Leaderboard and LightOn’s scores: the leaderboard ranking (October 2026) and LightOn’s published 74.6 (ParseBench) and 85.5 (olmOCR-bench) are for LightOnOCR-3 0.8B in LightOn’s own full-precision setup, not superPDF’s scores. superPDF runs it in the browser with 4-bit weights and 1,540-pixel page images, converted to superPDF’s Markdown and tables: 59.7 and 77.2% on our samples.
- Languages: in our tests, high-accuracy reading did not read Gujarati well.
- Other devices: phones and 8 GB laptops are slower.
