dots.ocr
Ranked 5 of 11 OCR models by recommenders
Open-source OCR model that people rank among the leading free options, well ahead of traditional OCR. Main caveat: it needs considerable computing resources.
Open-source OCR model that people rank among the leading free options, well ahead of traditional OCR. Main caveat: it needs considerable computing resources.
9 people gave an opinion
- recommend it
- 8
- criticize it
- 1
- approval share
- 89%
Recommended in 5 of 13 months
- November 2025: not recommended
- December 2025: recommended
- January 2026: recommended
- February 2026: recommended
- March 2026: recommended
- April 2026: not recommended
- May 2026: not recommended
- June 2026: not recommended
- July 2026: not recommended
- August 2026: recommended
- September 2026: not recommended
- October 2026: not recommended
- November 2026: not recommended (month in progress)
Why it doesn’t carry the badge
- 8 people recommend itNeeds 10 or more, not met.
- 8 recommenders for every criticNeeds 2 to 1 or better, met.
- Recommended in 5 of 13 monthsNeeds 4 or more, met.
The same three rules apply to every product, and the badge can’t be bought. How the badge works
What people say about it
The reasons people give, with the number of comments that give each one. Open a reason to read what they said.
Why people recommend it
Each mark is one comment
Leading open-source OCR model
“a number of other open source options like dots [1] or olmOCR [2] rank higher.”
Comment from 16 Feb 2026 in “Rolling your own serverless OCR in 40 lines of code” “one of the leading open-source OCR models on the market”
Comment from 16 Feb 2026 in “Rolling your own serverless OCR in 40 lines of code”
What people warn about
Each mark is one comment
Requires considerable computing resources
“dots.ocr requires requires a considerable amount of computational resources”
Comment from 21 Jan 2026 in “Show HN: Ocrbase – pdf → .md/.json document OCR and structured extraction API”
Other OCR models people recommend
The four most recommended other OCR models, with the same counts for each, so you can compare like for like. The tick on each bar marks the 2 to 1 line the badge needs.
| Product | Recommend | Criticize | Approval | Months | Owned | Badge |
|---|---|---|---|---|---|---|
| Mistral OCR | 69 | 40 | 63% | 12 | — | — |
| PaddleOCR | 19 | 4 | 83% | 8 | — | Approved |
| GLM-OCR | 16 | 4 | 80% | 7 | — | Approved |
| DeepSeek-OCR | 12 | 4 | 75% | 9 | — | Approved |
| dots.ocrThis page | 8 | 1 | 89% | 5 | — | — |
What people said
8 of the 10 comments that mention it, newest first. Each links to the original comment.
“performed significantly worse”
“one of the leading open-source OCR models on the market”
“a number of other open source options like dots [1] or olmOCR [2] rank higher.”
“dot-ocr in layout mode works best (but is slow)”
“If you have Mac device with ARM CPU(M series), you can try my dots.ocr.runner”
“dots.ocr requires requires a considerable amount of computational resources”
“I got fantastic results when I tested dots.”
“it's still streets ahead of traditional OCR techniques”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.