doctr alternatives
Curated alternatives to doctr — and why you'd switch.
TurboOCR
GPU document parser in C++/TensorRT: PP-OCRv6 OCR, layout, tables and formulas to Markdown at 200-559 img/s on one GPU — no VLM, HTTP + gRPC, one-line Docker deploy.
Why switchThe two non-VLM options, at different points on the effort curve: TurboOCR is a C++/TensorRT server doing 200-559 images/s with layout, tables and formulas to Markdown; docTR is a Python library you import, fine-tune and control architecture by architecture.
Full comparison →chandra
Datalab's SOTA open OCR model: images/PDFs to structured HTML/Markdown/JSON with layout, tables, forms, checkboxes, handwriting and math, in 90+ languages. Local HF or vLLM inference.
Why switchClassic pipeline versus one big model: Chandra is a VLM that reads a page into structured HTML/Markdown including handwriting and math; docTR runs small detection and recognition nets for word boxes. Chandra for structure, docTR for cost, determinism and fine-tuning.
Full comparison →olmocr
Open toolkit that linearizes messy PDFs — scans, tables, equations, handwriting — into clean ordered Markdown with a self-hosted vision-language model. Built for LLM training data and RAG ingestion.
Why switchBoth turn messy pages into text for downstream AI. olmOCR linearizes whole documents into ordered Markdown with a self-hosted VLM, aimed at training data and RAG ingestion; docTR stops at accurate word-level recognition you can build any layout logic on.
Full comparison →