Model comparison
GPT-5.6 Luna vs Nemotron 3 Nano 30B A3B
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 40.6 on the Noometry Index. Nemotron 3 Nano 30B A3B costs 5.1× less per token, which makes it the better buy when GPT-5.6 Luna's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
NVIDIASummary
- They share 17 benchmarks with published results for both. GPT-5.6 Luna scores higher in 8 categories and Nemotron 3 Nano 30B A3B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Luna leads 77.7 to 37.8.
- Nemotron 3 Nano 30B A3B is cheaper at $0.05 / $0.20 per million input/output tokens, against $0.20 / $1.20 for GPT-5.6 Luna.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 262K.
- Nemotron 3 Nano 30B A3B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.6 Luna | Nemotron 3 Nano 30B A3B | |
|---|---|---|
| Provider | OpenAI | NVIDIA |
| Noometry Index | 54.6 | 40.6 |
| Released | 2026-07-09 | 2025-12-15 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $0.20 | $0.05 |
| Output $ / M tokens | $1.20 | $0.20 |
| Results tracked | 52 | 18 |
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Category by category
Coding GPT-5.6 Luna leads
GPT-5.6 Luna: 54.5 (#28), Nemotron 3 Nano 30B A3B: 40.5 (#138)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Coding | 1466 | 1378 |
| DeepSWE | 67.2% | — |
| FrontierCode | 39.8% | — |
| CursorBench | 35.9% | — |
| LMArena WebDev | 1519 | — |
| SciCode | 53.6% | — |
| WeirdML | 60.9% | — |
| ALE-Bench | 1,667 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Luna: 34.4 (#45), Nemotron 3 Nano 30B A3B: —
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| APEX-Agents | 43% | — |
| BALROG | 45.6% | — |
| GDP.pdf | 22.7% | — |
| Vending-Bench 2 | 4,095 | — |
Reasoning GPT-5.6 Luna leads
GPT-5.6 Luna: 47.6 (#43), Nemotron 3 Nano 30B A3B: 27.1 (#124)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Hard Prompts | 1451 | 1348 |
| ARC-AGI-2 | 59.5% | — |
| SimpleBench | 46.8% | — |
| Kagi LLM Benchmark | 49.1% | — |
| NYT Connections (extended) | 69.4% | — |
| ARC-AGI-1 | 88% | — |
| CritPt | 20.6% | — |
| Chess Puzzles | 40% | — |
| Mystery Game Puzzles | 21% | — |
| DTBench | 89.1% | — |
| LMCA | 48.5% | — |
| Surface Evolver Bench | 61.9% | — |
| Epoch Capabilities Index | 156.39 | — |
Math GPT-5.6 Luna leads
GPT-5.6 Luna: 77.7 (#14), Nemotron 3 Nano 30B A3B: 37.8 (#147)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Math | 1458 | 1371 |
| FrontierMath (Tiers 1-3) | 82.1% | — |
| FrontierMath Tier 4 | 61% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 60% | — |
Knowledge GPT-5.6 Luna leads
GPT-5.6 Luna: 58.5 (#34), Nemotron 3 Nano 30B A3B: 38.2 (#148)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Expert | 1478 | 1355 |
| GPQA Diamond | 91.6% | — |
| SimpleQA Verified | 41% | — |
| Vectara Hallucination Rate | — | 9.6% |
Multimodal Not comparable
GPT-5.6 Luna: 42.7 (#28), Nemotron 3 Nano 30B A3B: —
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Vision | 1258 | — |
| Blueprint-Bench 2 | 22.6% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1457 | — |
Multilingual GPT-5.6 Luna leads
GPT-5.6 Luna: 52.8 (#78), Nemotron 3 Nano 30B A3B: 45.8 (#162)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Non-English | 1417 | 1320 |
| LMArena Chinese | 1470 | 1382 |
| LMArena French | 1456 | 1396 |
| LMArena German | 1454 | 1348 |
| LMArena Japanese | 1411 | 1268 |
| LMArena Korean | 1415 | 1269 |
| LMArena Russian | 1428 | 1303 |
| LMArena Spanish | 1448 | 1376 |
Instruction Following GPT-5.6 Luna leads
GPT-5.6 Luna: 75.6 (#57), Nemotron 3 Nano 30B A3B: 68.8 (#180)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Instruction Following | 1437 | 1304 |
Long Context GPT-5.6 Luna leads
GPT-5.6 Luna: 43.9 (#82), Nemotron 3 Nano 30B A3B: 39.5 (#175)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Longer Query | 1436 | 1300 |
Writing & Preference GPT-5.6 Luna leads
GPT-5.6 Luna: 68.0 (#29), Nemotron 3 Nano 30B A3B: 52.3 (#174)
| Benchmark | GPT-5.6 Luna | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Text | 1431 | 1348 |
| LMArena Creative Writing | 1396 | 1269 |
| LMArena Multi-Turn | 1434 | 1319 |
| EQ-Bench Creative Writing | 1829 | — |
| EQ-Bench 4 | 1156 | — |
Frequently asked questions
Is GPT-5.6 Luna better than Nemotron 3 Nano 30B A3B?
GPT-5.6 Luna is the stronger model overall, scoring 54.6 to 40.6 on the Noometry Index. Nemotron 3 Nano 30B A3B costs 5.1× less per token, which makes it the better buy when GPT-5.6 Luna's lead doesn't matter for your workload.
Which is cheaper, GPT-5.6 Luna or Nemotron 3 Nano 30B A3B?
Nemotron 3 Nano 30B A3B is cheaper. It lists at $0.05 per million input tokens and $0.20 per million output tokens; GPT-5.6 Luna lists at $0.20 and $1.20.
Is GPT-5.6 Luna or Nemotron 3 Nano 30B A3B better for coding?
GPT-5.6 Luna scores higher on coding benchmarks: 54.5 versus 40.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Luna does, with 1.05M tokens against 262K.
How many benchmarks do GPT-5.6 Luna and Nemotron 3 Nano 30B A3B share?
17 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and Nemotron 3 Nano 30B A3B has 18.