Compare / Nemotron 3 Nano 30B-A3B vs Nemotron 3 Nano Omni 30B-A3B
Nemotron 3 Nano 30B-A3B vs Nemotron 3 Nano Omni 30B-A3B
Updated November 2026
Verdict
Nemotron 3 Nano 30B-A3B scores higher on the Small LM Index: 64.4 vs 42.7. On the 4 benchmarks both labs report, Nemotron 3 Nano 30B-A3B wins 4 and Nemotron 3 Nano Omni 30B-A3B wins 0. Nemotron 3 Nano 30B-A3B is smaller: it needs about 20.3 GB of memory at 4-bit, against 22.4 GB for Nemotron 3 Nano Omni 30B-A3B. Only Nemotron 3 Nano 30B-A3B has a hosted API on OpenRouter ($0.10 per million tokens); the other has to be self-hosted.
Pick Nemotron 3 Nano 30B-A3B if…
- you want the strongest model overall
- you need precise instruction following
- you build agents that call tools
- you have limited memory (about 20.3 GB at 4-bit)
- you want a hosted API rather than running it yourself
- you work with long documents
- you want the more widely used model (more quantized builds and community support)
Pick Nemotron 3 Nano Omni 30B-A3B if…
- you need image input
Specifications
| Nemotron 3 Nano 30B-A3B | Nemotron 3 Nano Omni 30B-A3B | |
|---|---|---|
| Small LM Index | 64.4 (likely 62–66) | 42.7 (likely 30–56) |
| Lab | NVIDIA · United States | NVIDIA · United States |
| Released | 2025-12-15 | 2026-04-28 |
| Parameters | 31.6B (3.5B active, MoE) | 31.6B (3.5B active, MoE) |
| Memory at 4-bit | ~20.3 GB | ~22.4 GB |
| Context window | 1M tokens | 256K tokens |
| Input | text | text, image, audio, video |
| Reasoning | Hybrid (thinking on/off) | Always thinks |
| License | NVIDIA Open Model | NVIDIA Open Model |
| API price / 1M tokens | $0.10 ($0.060 in, $0.24 out) | Self-host only |
| Hugging Face downloads (30 days) | 1.6M | — |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Nemotron 3 Nano 30B-A3B | Nemotron 3 Nano Omni 30B-A3B |
|---|---|---|
| MMLU-Pro Knowledge | 78.3 | ≈ 65 |
| GPQA Diamond Knowledge | 73.0 | 46.9✓ |
| Humanity's Last Exam Reasoning | 10.6 | 4.8✓ |
| AIME Math | 89.1 | ≈ 48 |
| LiveCodeBench Coding | 68.3 | ≈ 39 |
| SWE-bench Verified Coding | 38.8 | ≈ 43 |
| τ²-Bench Agentic | 49.0 | 45.3✓ |
| IFBench Instruction following | 71.5 | 63.2✓ |
| AA-LCR Long context | — | 39.7✓ |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Nemotron 3 Nano 30B-A3B or Nemotron 3 Nano Omni 30B-A3B?
Nemotron 3 Nano 30B-A3B scores higher on the Small LM Index: 64.4 vs 42.7. On the 4 benchmarks both labs report, Nemotron 3 Nano 30B-A3B wins 4 and Nemotron 3 Nano Omni 30B-A3B wins 0.
Which is cheaper to run?
Only Nemotron 3 Nano 30B-A3B has a hosted API on OpenRouter ($0.10 per million tokens); the other has to be self-hosted. Nemotron 3 Nano 30B-A3B is smaller: it needs about 20.3 GB of memory at 4-bit, against 22.4 GB for Nemotron 3 Nano Omni 30B-A3B.
Which has the longer context window?
Nemotron 3 Nano 30B-A3B has the longer context window: 1M tokens against 256K.
Can I use Nemotron 3 Nano 30B-A3B and Nemotron 3 Nano Omni 30B-A3B commercially?
Both are released under the NVIDIA Open Model license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.