aiptimizer/TurboOCR

Health v2 · maintenance only

Flags: young

Adoption not part of the score

1043 stars · 100 forks observed · 2026-09-01

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

TurboOCR is an extremely fast GPU-accelerated document parser written in C++ that combines OCR, layout analysis, table extraction, and formula recognition to output Markdown. It uses TensorRT FP16 inference with PP-OCRv6 models and serves results over HTTP and gRPC APIs.

Use cases

• parse scanned documents to markdown at high throughput
• run OCR on a GPU server with an HTTP or gRPC API
• extract text, tables, and formulas from PDFs for RAG pipelines
• batch process millions of document images quickly
• self-host a fast OCR inference server on NVIDIA GPUs
• convert document images to structured markdown

When to choose

• you need maximum OCR throughput (hundreds of images per second) on NVIDIA hardware
• you want a self-hosted document parsing service with HTTP and gRPC APIs
• you need OCR plus layout, table, and formula extraction feeding a RAG pipeline
• you can deploy on Linux with CUDA/TensorRT

When to avoid

• you need CPU-only or non-NVIDIA GPU support (Metal/OpenVINO/ROCm backends are not shipped yet)
• you need a lightweight embedded OCR library rather than a server
• you require Windows or macOS deployment
• you need a pure Python OCR solution

Facets

service · maturity active

ocr pdf machine-learning llm-inference http-server rpc rag computer-vision artificial-intelligence pdf gpu-computing cpp self-hosted tensorrt pp-ocrv6 paddleocr fp16 grpc fastapi document-parsing inference-server nvidia text-recognition layout-analysis table-extraction formula-recognition markdown-output documents linux docker gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="aiptimizer/TurboOCR")