Compare / Nemotron 3.5 Lightning vs EXAONE 4.0 32B
Nemotron 3.5 Lightning vs EXAONE 4.0 32B
Updated November 2026
Verdict
Nemotron 3.5 Lightning scores higher on the Small LM Index: 63.6 vs 62.0, although their likely ranges overlap, so the lead is not certain. On the 2 benchmarks both labs report, Nemotron 3.5 Lightning wins 1 and EXAONE 4.0 32B wins 0. Both need about 22.4 GB of memory at 4-bit quantization. Only Nemotron 3.5 Lightning has a hosted API on OpenRouter ($0.049 per million tokens); the other has to be self-hosted.
Pick Nemotron 3.5 Lightning if…
- you want the strongest model overall
- you want a hosted API rather than running it yourself
- you work with long documents
Pick EXAONE 4.0 32B if…
- you want the more widely used model (more quantized builds and community support)
Specifications
| Nemotron 3.5 Lightning | EXAONE 4.0 32B | |
|---|---|---|
| Small LM Index | 63.6 (likely 55–71) | 62.0 (likely 59–65) |
| Lab | NVIDIA · United States | LG AI Research (EXAONE) · Rest of Asia |
| Released | 2026-08-11 | 2025-07-15 |
| Parameters | 31.6B (3.6B active, MoE) | 32B (dense) |
| Memory at 4-bit | ~22.4 GB | ~21.9 GB |
| Context window | 1M tokens | 131K tokens |
| Input | text | text |
| Reasoning | Always thinks | Hybrid (thinking on/off) |
| License | OpenMDW-1.1 | EXAONE License (non-commercial) |
| API price / 1M tokens | $0.049 ($0.025 in, $0.12 out) | Self-host only |
| Hugging Face downloads (30 days) | — | 14.8K |
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 3.5 Lightning | EXAONE 4.0 32B |
|---|---|---|
| MMLU-Pro Knowledge | 81.9 | 81.8 |
| GPQA Diamond Knowledge | 75.4 | 75.4 |
| AIME Math | ≈ 88 | 85.3 |
| LiveCodeBench Coding | ≈ 73 | 66.7 |
| SWE-bench Verified Coding | 51.6 | ≈ 49 |
| MMLU Knowledge | — | 92.3 |
| Multilingual MMLU Multilingual | — | 85.6 |
| IFEval Instruction following | — | 83.7 |
| BFCL Agentic | — | 63.9 |
| HMMT Math | — | 72.9 |
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 3.5 Lightning or EXAONE 4.0 32B?
Nemotron 3.5 Lightning scores higher on the Small LM Index: 63.6 vs 62.0, although their likely ranges overlap, so the lead is not certain. On the 2 benchmarks both labs report, Nemotron 3.5 Lightning wins 1 and EXAONE 4.0 32B wins 0.
Which is cheaper to run?
Only Nemotron 3.5 Lightning has a hosted API on OpenRouter ($0.049 per million tokens); the other has to be self-hosted. Both need about 22.4 GB of memory at 4-bit quantization.
Which has the longer context window?
Nemotron 3.5 Lightning has the longer context window: 1M tokens against 131K.
Can I use Nemotron 3.5 Lightning and EXAONE 4.0 32B commercially?
Nemotron 3.5 Lightning is released under OpenMDW-1.1 and EXAONE 4.0 32B under EXAONE License (non-commercial). Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.