On Tuesday, NVIDIA introduced its new Llama Nemotron Nano VL, a brand new multimodal vision-language mannequin (VLM) that now leads the OCRBench v2 benchmark, highlighting its accuracy in doc evaluation throughout enterprise use instances.
Designed for clever doc processing, the mannequin reads and extracts knowledge from advanced layouts comparable to invoices, tables, graphs, and dashboards. It combines visible and textual reasoning capabilities, enabling it to parse numerous file sorts utilizing only a single GPU.
OCRBench v2, which assessments AI fashions on real-world monetary, authorized, and healthcare paperwork, confirmed Nemotron Nano VL’s superior efficiency in textual content recognition, chart parsing, and aspect recognizing. The benchmark consists of 10,000 human-verified Q&A pairs and 31 situation sorts. The NVIDIA mannequin may be seen topping the leaderboard chart.
Constructed on NVIDIA’s C-RADIO v2 imaginative and prescient encoder and educated utilizing Megatron and Energon infrastructure, the mannequin advantages from NeMo Retriever Parse knowledge and multimodal datasets developed by NVIDIA analysis groups. It’s out there as an API through NVIDIA NIM and for obtain on Hugging Face.
With help to be used instances like contract evaluation, compliance evaluation, and scientific report parsing, Llama Nemotron Nano VL is geared toward companies searching for scalable, cost-efficient AI for doc workflows. “This production-ready mannequin is designed for scalable AI brokers that learn and extract insights from multimodal paperwork with unmatched pace, bringing imaginative and prescient language fashions (VLMs) to the forefront of enterprise knowledge processing,” the corporate said within the weblog publish.
The launch expands NVIDIA’s Nemotron household and underscores its push into vision-language fashions tailor-made for enterprise knowledge intelligence.
Just lately, Mistral AI unveiled its new enterprise-grade Doc AI platform, designed to deal with advanced OCR duties with 99%+ accuracy throughout 11 languages. Able to parsing the whole lot from handwritten notes to low-resolution scans, the system converts paperwork into structured JSON, providing speeds of as much as 2,000 pages per minute on a single GPU.
The platform is provided to deal with intricate layouts like tables, kinds, and contracts, and helps each on-premise and personal cloud deployments for data-sensitive sectors. It stays to be seen how NVIDIA’s new VLM compares to it.
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