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OCR Speed Benchmark Update: April 2026

Updated April 2026 OCR speed benchmarks for self-hosted models across GPUs. Covers PaddleOCR, Surya, GOT-OCR 2.0, and DocTR with pages-per-minute throughput and accuracy data.

OCR Benchmark Update Overview

Document processing throughput directly impacts how quickly you can digitise archives, process invoices, or extract data from forms. This April 2026 benchmark update measures OCR speed across the leading open-source models on GigaGPU dedicated servers, using a standardised test set of 500 mixed document pages.

For the interactive benchmark tool, visit the OCR speed benchmarks page. This article highlights the key findings from the April 2026 test cycle.

Speed Results by Model and GPU

Pages per minute on mixed document types (invoices, letters, forms, tables):

Model RTX 3090 RTX 5090 RTX 5090 RTX 6000 Pro
PaddleOCR v4 85 pg/min 140 pg/min 195 pg/min 125 pg/min
Surya 42 pg/min 72 pg/min 98 pg/min 65 pg/min
GOT-OCR 2.0 35 pg/min 58 pg/min 82 pg/min 52 pg/min
DocTR 48 pg/min 80 pg/min 110 pg/min 72 pg/min
EasyOCR 55 pg/min 92 pg/min 125 pg/min 82 pg/min

PaddleOCR v4 remains the speed leader, processing 140 pages per minute on an RTX 5090. The RTX 5090 provides a meaningful 35-40% speed uplift across all models.

Accuracy vs Speed Trade-offs

Model Speed (RTX 5090) Overall F1 Table Accuracy VRAM Used
PaddleOCR v4 140 pg/min 93.5% 89.8% 2.8 GB
GOT-OCR 2.0 58 pg/min 96.1% 94.5% 8.5 GB
Surya 72 pg/min 94.8% 91.2% 4.2 GB
DocTR 80 pg/min 92.0% 87.3% 3.5 GB

GOT-OCR 2.0 delivers the highest accuracy but at the cost of speed and VRAM. For high-volume processing where 93%+ accuracy suffices, PaddleOCR v4 provides the best throughput. For accuracy-critical applications like financial documents, GOT-OCR 2.0 justifies the slower speed.

Batch Processing Throughput

Processing 10,000 pages end-to-end, including loading and post-processing:

Model / GPU Total Time Effective Throughput
PaddleOCR v4 / RTX 5090 78 min 128 pg/min
GOT-OCR 2.0 / RTX 5090 185 min 54 pg/min
Surya / RTX 5090 148 min 68 pg/min

Batch throughput is slightly lower than peak per-page speed due to overhead from loading pages and writing results. For large-scale document processing projects, see the document processing throughput benchmark.

Cost per Page by Configuration

Based on GigaGPU hosting rates, running 24/7:

Configuration Pages/Month Cost per Page
PaddleOCR / RTX 3090 ($175/mo) 3.67M $0.000048
PaddleOCR / RTX 5090 ($250/mo) 6.05M $0.000041
GOT-OCR 2.0 / RTX 5090 ($250/mo) 2.33M $0.000107

Self-hosted OCR costs a fraction of a cent per page, orders of magnitude cheaper than cloud OCR APIs. Detailed cost modelling available in the OCR cost per 10,000 pages guide.

Process Documents at Scale on Your Own Hardware

Self-hosted OCR with no per-page fees. Process millions of documents monthly on a dedicated GPU server.

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Recommendations

For maximum throughput on large document batches, PaddleOCR v4 on an RTX 5090 delivers the best pages-per-dollar. For complex documents requiring table extraction and layout understanding, GOT-OCR 2.0 justifies the additional cost. Both models leave substantial VRAM available for co-locating an open-source LLM for intelligent document processing pipelines.

Review the best OCR models guide for model selection and the GPU comparisons for hardware recommendations. Track the benchmarks section for future updates.

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