TurboOCR alternatives
Curated alternatives to TurboOCR — and why you'd switch.
MinerU
Heavyweight document-to-markdown/JSON parser — PDFs plus Office (docx/pptx/xlsx) through layout analysis and OCR into LLM-ready output for RAG and agentic pipelines. 73k stars, self-hostable.
Why switchSame job — documents to LLM-ready Markdown. MinerU is the heavyweight Python pipeline with Office support; TurboOCR trades breadth for 200+ img/s on one GPU.
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 switcholmOCR linearizes messy PDFs with a self-hosted VLM; TurboOCR refuses the VLM entirely and wins ~20x on throughput. Pick by corpus: pristine forms → TurboOCR, chaotic scans → VLM.
Full comparison →doctr
docTR: two-stage OCR in PyTorch — detect words, then recognize them — with pretrained detection and recognition architectures you can mix, plus layout detection and rotated-page handling.
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 →