HF Model & Benchmark Matrix

24,078 variants · 14,984 scores · 120 benchmarks

NVIDIA-Nemotron-Nano-9B-v2-NVFP4

nvidia/NVIDIA-Nemotron-Nano-9B-v2-NVFP4

kind
nvfp4
quant
nvfp4 (4-bit)
family
nemotron
modality
text-generation
root model
nvidia/NVIDIA-Nemotron-Nano-9B-v2
provider
nvidia
license
other
language
en, es, fr, de, it, ja
context
128K
library
transformers
vRAM (GB)
—
size on disk
—
downloads
12,753
likes
26
created
—
last modified
2026-01-08T19:23:43+00:00 (2026)
huggingface
https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2-NVFP4
tags
transformerssafetensorsnemotron_htext-generationnvidiapytorchconversationalcustom_codeenesfrdeitjadataset:nvidia/Nemotron-Post-Training-Dataset-v1dataset:nvidia/Nemotron-Post-Training-Dataset-v2dataset:nvidia/Nemotron-Pretraining-Dataset-sampledataset:nvidia/Nemotron-CC-v2dataset:nvidia/Nemotron-CC-Math-v1dataset:nvidia/Nemotron-Pretraining-SFT-v1arxiv:2504.03624arxiv:2508.14444arxiv:2412.02595base_model:nvidia/NVIDIA-Nemotron-Nano-9B-v2

Benchmark scores (6)

benchmarkcategoryscorecontextconfevidence
MATH-500math96.3MATH500medium| MATH500 | 96.3% | 97.8% | 97.5% | 97.2% |
IFEvalinstruction-following89.4IFEval (Instruction Strict)medium| IFEval (Instruction Strict) | 89.4% | 90.3% | 90.2% | 89.3% |
RULERlong-context74.1RULER (128K)medium| RULER (128K) | 74.1% | 78.9% | 76.1% | 75.0% |
AIME 2025math69.3AIME25medium| AIME25 | 69.3% | 72.1% | 71.3% | 71.5% |
BFCL (function calling)agentic66.3BFCL v3medium| BFCL v3 | 66.3% | 66.9% | 65.7% | 65.9% |
GPQAreasoning59.6GPQAmedium| GPQA | 59.6% | 64.0% | 60.6% | 62.7% |

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Hugging Face model & benchmark data scraped & matrix-ified. 24,078 variants · 14,984 scores · 120 benchmarks.