Active Parameters
3.5B
Context Length
1M
Modality
Text
Architecture
Mixture of Experts
KV Cache Rate
52 KB/tok
License
NVIDIA Open Model License
Release Date
15 Dec 2025
Knowledge Cutoff
Nov 2025
API Pricing (per 1M)
Input: $0.06 · Output: $0.24
Precision
Context
Workload Memory: 18.51 GB
INT4 · 8K context
Base Weights: 15.60 GB
KV Cache: 0.41 GB
Runtime & Graphs: 2.50 GB
1x NVIDIA L4 24GB
18.5 / 21.6 GB usable
2x RTX 4090 24GB
18.5 / 43.2 GB usable · TP 2
Apple M3 Pro 36GB
18.5 / 27.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Rank
#148
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.783 | 33 |
Graduate-Level QA | 0.75 | 76 |
Agentic Index | auto 1 | 115 |
Coding Index | 0.14 | 141 |
General Text | 1314 | 162 |
Intelligence Index | auto 0.09 Standard 0.07 | 247 274 |
Overall Rank
#148
Coding Rank
#144
Nemotron 3 Nano 30B-A3B is an open hybrid MoE model from NVIDIA combining Mamba-2 state-space layers with attention for efficient long-context execution. It activates 6 experts across a 1M context window for high-speed agentic systems.
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
2
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
10,000
Normalization
RMS Normalization
Activation Function
ReLU2
Dimensions
Hidden Dimension Size
2,688
Number of Layers
52
FFN Intermediate Size (Dense)
1,856
Tokenizer
Vocabulary Size
131,072
Mixture of Experts
Total Expert Parameters
30.0B
Number of Experts
129
Active Experts
6
Shared Experts
1
FFN Intermediate Size (per Expert)
1,856
Nemotron 3 is NVIDIA's family of open models delivering leading efficiency and accuracy for agentic AI applications. Utilizing hybrid Mamba-Transformer MoE architecture with Latent MoE design, the models support up to 1M token context and feature Multi-Token Prediction for improved generation efficiency. The Nano variant outperforms comparable models while maintaining extreme cost-efficiency.