Skip to content 
The fastest method for installing this model locally is by using Docker.
Kindly follow the on-screen instructions below.
The loader auto-caches the model archive (several GBs included).
The installer diagnoses your environment to deploy the most compatible profile.
olmOCR-2-7B-1025-FP8 delivers state‑of‑the‑art optical character recognition with a massive 7‑billion parameter base, enabling unprecedented accuracy on complex document layouts. Built on the FP8 quantization scheme, it achieves a balanced trade‑off between inference speed and memory footprint, making it suitable for both cloud and edge deployments. The architecture incorporates a refined vision encoder that processes high‑resolution scans up to 1025 × 1025 pixels, preserving fine glyphs and contextual spacing. A dedicated language model head leverages multilingual tokenizers, supporting over 100 languages while maintaining a low error rate on cursive and printed text. Benchmark results show a 3.2 % absolute gain over the previous generation on the PubLayNet dataset, and the model is openly released under an permissive license for research and commercial use.
| Model | olmOCR-2-7B-1025-FP8 |
| Parameters | 7 B |
| Input Resolution | 1025 × 1025 |
| Quantization | FP8 |
| Supported Languages | 100+ |
| License | Permissive (Apache 2.0) |
- Script automating installation of Open-WebUI docker templates with data persistence
- How to Setup olmOCR-2-7B-1025-FP8 via WebGPU (Browser) 5-Minute Setup FREE
- Script downloading specialized multi-column layout parsing models for PDF engines
- Full Deployment olmOCR-2-7B-1025-FP8 Locally via Ollama 2 For Low VRAM (6GB/8GB) Local Guide FREE
- Downloader pulling optimized model shards for limited bandwith setups
- How to Autostart olmOCR-2-7B-1025-FP8 Zero Config Local Guide
- Installer deploying deep semantic index tools requiring zero cloud connections
- Full Deployment olmOCR-2-7B-1025-FP8 100% Private PC with 1M Context Offline Setup
