OmniParse vs text-extract-api
Self-hosted document and media extraction compared
OmniParse and text-extract-api are self-hostable Python services that turn files into structured output for AI workflows. OmniParse covers documents, media, and web pages, while text-extract-api focuses on document extraction with optional model processing, PII-removal prompts, and workflow features such as caching and storage profiles.
OmniParse: Turn Documents and Media into AI-Ready Data
OmniParse is a self-hosted Python service that converts documents, images, audio, video, and web pages into structured output for GenAI workflows. It suits teams building ingestion pipelines that want local parsing, but requires Linux and a GPU with at least 8–10 GB of VRAM.
text-extract-api: Extract Text and Data from Documents
A self-hostable API that turns PDFs, images, and Office files into Markdown or structured JSON using OCR and Ollama models. It suits teams that need document processing and PII removal with control over where files are processed.
| OmniParse | text-extract-api | |
|---|---|---|
| Language | Python | Python |
| License | GPL-3.0 | MIT |
| Stars | 7.9k | 3.2k |
| Forks | 675 | 279 |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- OmniParse handles documents, images, audio, video, and web pages; text-extract-api focuses on PDFs, images, and Office documents.
- OmniParse outputs structured Markdown and supports transcription and web crawling; text-extract-api produces Markdown or JSON and can refine OCR output with Ollama models.
- OmniParse requires Linux and a GPU with at least 8–10 GB of VRAM for its deep-learning models; text-extract-api documents a stack including FastAPI, Celery, Redis, and Ollama, with resource needs varying by OCR strategy and model.
- OmniParse is licensed under GPL-3.0; text-extract-api is licensed under MIT, with separate licensing terms to review for some model and service options in both projects.
- OmniParse offers an HTTP API and Gradio UI; text-extract-api offers an HTTP API, CLI, and TypeScript client.
- OmniParse has 7.9k stars and 675 forks; text-extract-api has 3.2k stars and 279 forks. Both are unarchived.
Choose OmniParse if you…
- need to process audio, video, or web pages alongside documents and images.
- want a local API and interactive UI for preparing mixed-format content for AI workflows.
- have a Linux environment and a GPU with at least 8–10 GB of VRAM available.
Choose text-extract-api if you…
- need to extract document content as Markdown or structured JSON.
- want optional Ollama processing, prompt-based PII removal, or configurable OCR strategies.
- need asynchronous processing, OCR-result caching, or configurable result storage such as local files, Google Drive, or Amazon S3.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.