PaddleOCR vs EasyOCR vs Doctr: Memory & Latency Test

#ocr #paddleocr #easyocr #doctr

The 800MB Surprise

I spun up three OCR engines on the same 1000-image dataset and watched htop. PaddleOCR sat at 450MB idle, EasyOCR at 800MB, Doctr at 320MB. That's before a single inference call.

This isn't about which engine reads text better — I already tested accuracy across 10,000 images. This is about whether your production API stays under the memory limit when 20 concurrent requests hit at once. The difference between an engine that loads in 2 seconds versus 18 seconds isn't academic when you're running serverless functions with cold start penalties.

I ran each engine through the same gauntlet: initialization time, first inference latency, steady-state memory footprint, and batch processing throughput. The results clarify when each tool makes sense — and when your hosting bill will triple because you picked wrong.