NVIDIA Nemotron 3 Nano 30B-A3B
Active Parameters
3.5B
Context Length
1M
Modality
Text
Architecture
Mixture of Experts (MoE)
License
NVIDIA Open Model License
Release Date
15 Dec 2025
Knowledge Cutoff
Nov 2025
API Pricing (per 1M)
Input: $0.06 · Output: $0.24
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
1,000,000 tokens
Consumer
3x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#120
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.783 | 31 |
Graduate-Level QA | 0.75 | 71 |
Agentic Index | 0.02 | 117 |
General Text | 1314 | 128 |
Coding Index | auto 0.14 | 132 |
Intelligence Index | auto 0.14 Standard 0.07 | 201 237 |
Rankings
Overall Rank
#120
Coding Rank
#117
About NVIDIA Nemotron 3 Nano 30B-A3B
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.
Technical Specifications
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
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
ReLU2
Dimensions
Hidden Dimension Size
2,688
Number of Layers
52
FFN Intermediate Size (Dense)
1,856
Multi-Token Prediction Heads
-
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
Dense Layers Before MoE
-
About Nemotron 3
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.
Other Nemotron 3 Models
- No related models available