NVIDIA-Nemotron-Nano-12B-v2-VL-NVFP4-QAD
nvidia/NVIDIA-Nemotron-Nano-12B-v2-VL-NVFP4-QAD
Tracked by OpenModelStats since September 8, 2026View on Hugging Face ↗
- Downloads 30DRolling recent-window download count as reported by the source platform.
- 169.2K
- Total downloadsCumulative all-time download counter reported by the source platform.
- 478.2K
- Gained 7DIncrease in cumulative total downloads between OpenModelStats' own observations seven days apart.
- +3,208(increase)
- 1.0%(up) vs baseline
- Gained 30DIncrease in cumulative total downloads between OpenModelStats' own observations roughly thirty days apart.
- —
- LikesCommunity likes reported by the source platform.
- 32
- +0 in 7D
- Rank · tracked modelsPosition among all eligible models tracked by OpenModelStats, ordered by recent downloads. #285 among tracked Image Text to Text models.
- #1,834
- 225(up 225 places)this week
- Parameters
- 7.7B
- Last source update
- Sep 2, 2026
- MomentumOpenModelStats' composite rising-model signal (0–100): a percentile blend of absolute 7-day download gains, capped percentage growth, and likes gained. See Methodology.
- 58.5
- NVIDIA-Nemotron-Nano-12B-v2-VL-NVFP4-QAD gained 3,208 downloads during the last seven tracked days.
- It moved from #311 to #285 among tracked Image Text to Text models this week.
Downloads over time
Cumulative total downloads observed by OpenModelStatsLikes over time
Rank among tracked models
Lower is betterOverview
NVIDIA-Nemotron-Nano-12B-v2-VL-NVFP4-QAD is a image text to text model published by nvidia. OpenModelStats has tracked the model since Sep 8, 2026, most recently observing it 4h ago.
- Published
- Oct 22, 2025
- Last updated
- Sep 2, 2026
- Library
- transformers
- License
- other
- Task
- Image Text to Text
- Parameters
- 7,699,118,592
- Spaces
- —
- Derivative models
- —
- Velocity 7D/day
- 458
transformerssafetensorsNemotronH_Nano_VL_V2feature-extractionnvidiaVLMFP4image-text-to-textconversationalcustom_codearxiv:2501.14818arxiv:2511.03929
Publisher
nvidiaView publisher statistics →Similar models
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