NVIDIA
NVIDIA-Nemotron-Nano-9B-v2-Base is a large language model (LLM) trained from scratch by NVIDIA that is designed as a completion model for a given piece of text. It uses a hybrid model architecture that consists primarily of Mamba-2 and MLP layers combined with just four Attention layers.
Running this yourself: desktop gpu should be enough.
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32.8
Quality Score
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Arena ELO
9B
Parameters
131K
Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
17 of 22 public signals
Use this section to answer one simple question first: how much outside evidence do we have that this model performs well? Structured benchmark scores appear first, then official provider evidence, then live arena signal.
This model has official provider benchmark evidence, but not a normalized independent benchmark table yet.
A full normalized benchmark row is not available for this model yet.
Official benchmark evidence is already available below, so this release is still being tracked while the normalized table catches up.
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3.0K
Downloads
46
Likes
Aug 2025
Released
5/5 signals
2/4 signals
4/5 signals
3/4 signals
3/4 signals
Parameters
9B
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources
These are recent benchmark or leaderboard claims from official provider sources. They are useful for freshness and context, but they are not treated the same as normalized independent benchmark rows.
nvidia/NVIDIA-Nemotron-Nano-9B-v2-Base · Hugging Face
NVIDIA published benchmark or leaderboard evidence for NVIDIA-Nemotron-Nano-9B-v2-Base.
View sourcenvidia/NVIDIA-Nemotron-Nano-9B-v2-Base · Hugging Face
NVIDIA published benchmark or leaderboard evidence for NVIDIA-Nemotron-Nano-9B-v2-Base.
View source