Compare / EXAONE 4.0 32B vs Nemotron 3 Nano Omni 30B-A3B
EXAONE 4.0 32B vs Nemotron 3 Nano Omni 30B-A3B
Updated November 2026
Verdict
EXAONE 4.0 32B scores higher on the Small LM Index: 61.9 vs 42.7. On the 4 benchmarks both labs report, EXAONE 4.0 32B wins 2 and Nemotron 3 Nano Omni 30B-A3B wins 2. Both need about 22.4 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.
Pick EXAONE 4.0 32B if…
- you want the strongest model overall
- you want the more widely used model (more quantized builds and community support)
Pick Nemotron 3 Nano Omni 30B-A3B if…
- you need precise instruction following
- you build agents that call tools
- you work with long documents
- you need image input
Specifications
| EXAONE 4.0 32B | Nemotron 3 Nano Omni 30B-A3B | |
|---|---|---|
| Small LM Index | 61.9 (likely 60–64) | 42.7 (likely 30–56) |
| Lab | LG AI Research (EXAONE) · Rest of Asia | NVIDIA · United States |
| Released | 2025-07-15 | 2026-04-28 |
| Parameters | 32B (dense) | 31.6B (3.5B active, MoE) |
| Memory at 4-bit | ~21.9 GB | ~22.4 GB |
| Context window | 131K tokens | 256K tokens |
| Input | text | text, image, audio, video |
| Reasoning | Hybrid (thinking on/off) | Always thinks |
| License | EXAONE License (non-commercial) | NVIDIA Open Model |
| API price / 1M tokens | Self-host only | Self-host only |
| Hugging Face downloads (30 days) | 15.1K | — |
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 | EXAONE 4.0 32B | Nemotron 3 Nano Omni 30B-A3B |
|---|---|---|
| MMLU-Pro Knowledge | 81.8✓ | ≈ 65 |
| GPQA Diamond Knowledge | 73.9✓ | 46.9✓ |
| Humanity's Last Exam Reasoning | 11.4✓ | 4.8✓ |
| AIME Math | 84.3✓ | ≈ 48 |
| LiveCodeBench Coding | 74.7✓ | ≈ 39 |
| τ²-Bench Agentic | 17.3✓ | 45.3✓ |
| IFBench Instruction following | 36.3✓ | 63.2✓ |
| MMLU Knowledge | 92.3 | — |
| Multilingual MMLU Multilingual | 85.6 | — |
| IFEval Instruction following | 83.7 | — |
| BFCL Agentic | 63.9 | — |
| MATH-500 Math | 97.7✓ | — |
| HMMT Math | 72.9 | — |
| 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, EXAONE 4.0 32B or Nemotron 3 Nano Omni 30B-A3B?
EXAONE 4.0 32B scores higher on the Small LM Index: 61.9 vs 42.7. On the 4 benchmarks both labs report, EXAONE 4.0 32B wins 2 and Nemotron 3 Nano Omni 30B-A3B wins 2.
Which is cheaper to run?
Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 22.4 GB of memory at 4-bit quantization.
Which has the longer context window?
Nemotron 3 Nano Omni 30B-A3B has the longer context window: 256K tokens against 131K.
Can I use EXAONE 4.0 32B and Nemotron 3 Nano Omni 30B-A3B commercially?
EXAONE 4.0 32B is released under EXAONE License (non-commercial) and Nemotron 3 Nano Omni 30B-A3B under NVIDIA Open Model. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.