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Beating AI Express News: Jina AI has released its document parsing model jina-ocr-v1, which can directly convert PDFs, scanned documents, tables, and charts into Markdown. Post-trained on DeepSeek-OCR, the model retains the latter’s Mixture of Experts (MoE) architecture with approximately 3.4 billion total parameters, activating around 570 million parameters per token during decoding, and integrates FastMTP speculative decoding. In Jina’s internal tests, jina-ocr-v1 scored 91.14 on OmniDocBench v1.6, 0.89 points higher than DeepSeek-OCR-2; it also achieved 83.4 on olmOCR-Bench, a 7.4-point improvement over the DeepSeek-OCR base model it is built on. Throughput is one of Jina’s key selling points: on a single A100 with 32 concurrent requests, the model delivers 2.57 pages per second — the highest among the 14 systems Jina benchmarked, roughly 22% faster than DeepSeek-OCR’s 2.10 pages per second. The model weights are now available on Hugging Face under the CC BY-NC 4.0 license; commercial use requires contacting Jina.
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