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Daily blended price ($/1M) — recorded each day, builds into a trend over time.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-11 · Source: nvidia_reference_catalog
Mixed text, image, audio and document workloads that benefit from one model across modalities.
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 transfor...
nemotron-nano-12b-v2-vl is a Multimodal model from NVIDIA (US). HotON.ai tracks it at $0.20 per 1M input tokens and $0.60 per 1M output tokens, with a 131K-token context window. Its composite efficiency score is 89/100 at an estimated $0.001 per successful task.
nemotron-nano-12b-v2-vl is tracked at $0.20 per 1M input tokens and $0.60 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.50 per 1M tokens. Figures are illustrative demo data.
Mixed text, image, audio and document workloads that benefit from one model across modalities.
nemotron-nano-12b-v2-vl supports up to a 131K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, nemotron-nano-12b-v2-vl is cheaper than 62% of models on input price and ranks #233 of 535 by overall efficiency.
Yes — grok-4-fast is a lower-cost option at $0.50 per 1M output tokens, while still covering similar Multimodal use cases. Compare them side by side on HotON.ai.
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HotON.ai — nemotron-nano-12b-v2-vl (NVIDIA): $0.20/1M input, $0.60/1M output, as of 2026-05-11. https://hoton.ai/en/models/nvidia-nemotron-nano-12b-v2-vlPricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.