Jina AI releases jina-ocr-v1 document parser
The open-source model achieves high accuracy and speed on low-budget GPUs using speculative decoding.
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In short: Jina AI was acquired by Elastic, capping a wave of releases spanning OCR, multimodal embeddings, rerankers, and vision-language models.
The open-source model achieves high accuracy and speed on low-budget GPUs using speculative decoding.
The 0.6B reranker beats Qwen3-4B on BEIR using hybrid attention and self-distillation, offering up to 1.56x faster speed than v3.
The model supports text, image, audio and video in a single space, matching larger models at 5.7x fewer parameters.
The tech blog introduces the jina-ai/audio-embedding-kickstarter, a module combination approach that beats CLAP with 25x less data using multimodal LLMs.
Dongcha Beating AI Flash News: Jina AI has released the document parsing model jina-ocr-v1, which can directly convert PDFs, scanned documents, tables, and charts into Markdown. It is based on post-training of DeepSeek-OCR, retaining its MoE architecture with approximately 3.4 billion total parameters and about 570 million parameters activated per token during decoding, and incorporates FastMTP speculative decoding. In Jina's self-tests, jina-ocr-v1 achieved top performance in OmniDocBench...
Elastic (NYSE: ESTC), the Search AI Company, has completed the acquisition of Jina AI, a pioneer in open source multimodal and multilingual embeddings, reranker, and...
Elastic (ESTC) is in focus after introducing jina-embeddings-v5-omni, a multimodal embedding family...
On October 10, real-time search leader Elastic completed the acquisition of Jina AI, a pioneer in the field of open-source multimodal and multilingual embeddings, rerankers, and small language models. This acquisition deepens Elastic's capabilities in vector search, retrieval-augmented generation ...
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