OmniParse vs marker
Self-hosted AI data ingestion compared
OmniParse and marker are Python projects that convert documents into structured content for AI workflows. OmniParse handles a wider range of inputs, including media and web pages, while marker focuses on document conversion and offers several output formats and processing options.
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.
marker: Convert Documents into Structured Text
Marker converts PDFs and other documents into Markdown, JSON, HTML, or chunks, preserving structure such as tables, equations, and images. It suits developers building document-processing workflows who can run its local models and inference backend.
| OmniParse | marker | |
|---|---|---|
| Language | Python | Python |
| License | GPL-3.0 | Apache-2.0 |
| Stars | 7.9k | 40.2k |
| Forks | 675 | 2.9k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- OmniParse processes documents, images, audio, video, and web pages; marker focuses on PDFs and other supported document formats.
- OmniParse produces structured Markdown and includes transcription and web crawling; marker outputs Markdown, JSON, HTML, or chunks and processes elements such as equations, code, and links.
- OmniParse requires Linux and a GPU with at least 8–10 GB of VRAM; marker supports different inference setups, including CPU and Apple Silicon through llama.cpp.
- OmniParse is licensed under GPL-3.0, while marker's code is Apache-2.0 licensed; both projects note separate model-weight licensing terms that may limit some commercial uses.
- OmniParse offers an HTTP API and Gradio UI; marker provides a CLI, Python API, and a local server described as suitable for small-scale use.
- OmniParse has 7.9k stars and 675 forks; marker has 40.2k stars and 2.9k forks.
Choose OmniParse if you…
- need to ingest media and web pages alongside documents.
- want transcription, OCR, or web crawling in a local ingestion service.
- can run the service on Linux with a GPU meeting its stated VRAM requirement.
Choose marker if you…
- need document outputs in Markdown, JSON, HTML, or chunks.
- want options such as batch CLI conversion, custom processors, or fast and balanced modes.
- need a local document workflow and can configure its inference backend for your hardware and workload.
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.