Nvidia Nemotron Nano 12B V2 Vl, developed by NVIDIA, features 12B parameters and 131k-token context window. NVIDIA Nemotron Nano 2 VL is a 12-billion-parameter open multimodal reasoning model designed for video understanding and document intelligence. It introduces a hybrid Transformer-Mamba architecture, combining transformer-level accuracy with Mamba’s memory-efficient sequence modelling for significantly higher throughput and lower latency. The model supports inputs of text and multi-image documents, producing natural-language outputs. It is trained on high-quality NVIDIA-curated synthetic datasets optimised for optical-character recognition, chart reasoning, and multimodal comprehension. Nemotron Nano 2 VL achieves leading results on OCRBench v2 and scores ≈ 74 average across MMMU, MathVista, AI2D, OCRBench, OCR-Reasoning, ChartQA, DocVQA, and Video-MME, surpassing prior open VL baselines. With Efficient Video Sampling (EVS), it handles long-form videos while reducing inference cost. Open-weights, training data, and fine-tuning recipes are released under a permissive NVIDIA open license, with deployment supported across NeMo, NIM, and major inference runtimes. Available at $0.2/1M tokens.
Visit NVIDIA: Nemotron Nano 12B 2 VLAI-Powered
Leverages advanced AI technology to deliver cutting-edge capabilities and results.
Fast & Efficient
Optimized performance ensures quick results without compromising on quality.
Purpose-Built
Specifically designed for llms tasks and workflows.
Nvidia Model Timeline
256k tokens context
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128k tokens context
131k tokens context
131k tokens context
128k tokens context
131k tokens context
131k tokens context
131k tokens context
Specifications
AI Evaluation
Compact but capable, this reasoning-focused model handles complex logical tasks efficiently. A good balance of analytical power and resource efficiency.
Pros
- Competitive pricing ($0.2/1M)
- 131k token context window
- Advanced logical reasoning
- Video content understanding
Cons
- API integration required
- May need prompt tuning
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