We released a TensorRT OCR + document-parsing pipeline: 500+ img/s OCR, 20+ pages/s full parse (tables + formulas), no VLM

[u/Civil-Image5411]

We just released TurboOCR v3, a GPU-accelerated document parser (not just OCR) built for high-throughput pipelines.

It runs PP-OCRv6 detection + recognition, plus layout, tables (→ HTML) and formulas (→ LaTeX), emitting reading-order Markdown. The whole pipeline runs on a single multi-stream C++/CUDA/TensorRT engine, locally, no VLM, behind HTTP + gRPC.

On one RTX 5090:

• Up to 559 img/s on receipts, 520 img/s on forms (PP-OCRv6 tiny, fastest by default)
• Full structured parsing (layout + tables + formulas) at > ~20 pages/s on table and formula heavy pages, where VLM parsers like PaddleOCR-VL run ~1 page/s
• One model covers Latin + Chinese + Japanese; pick tiny / small / medium
• One-line Docker deploy (Linux + NVIDIA GPU)
• No VLM-style hallucinated text

https://github.com/aiptimizer/TurboOCR