Jina AI Releases jina-ocr-v1: A 3.4B MoE Document Parser With Built-In Speculative Decoding for Low-Budget GPUs
Jina AI, part of Elastic, has released jina-ocr-v1, an end-to-end visual document parser. It takes PDFs, scans, tables, charts or invoices and returns clean Markdown in 1 pass. The model has 3.4B total parameters, with about 570M decoder parameters active per token. A speculative decoding head ships inside the checkpoint. Jina AI built it to serve on low-budget GPUs such as the NVIDIA L4. The technical report lists 91.14 on OmniDocBench v1.6 and 83.4 on olmOCR-Bench. Is it deployable? Yes, f
Jina AI released jina-ocr-v1, a document parser model that converts PDFs, scans, tables, charts, and invoices into formatted Markdown text in a single pass. The model contains 3.4 billion total parameters with about 570 million active per token and includes a built-in speculative decoding feature designed to run efficiently on lower-cost GPUs. The model scores 91.14 on OmniDocBench v1.6 and 83.4 on olmOCR-Bench, achieving the highest throughput of 2.57 pages per second when measured against 14 other systems. The open weights are available under a CC BY-NC 4.0 license, which permits research and non-commercial use but requires contacting Jina AI for commercial deployment.
Explainer: Why AI Is Getting Faster Without Getting Smarter: Speculative Decoding Explained
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