GPT-5.6 Luna vs Nemotron 3 Ultra
GPT-5.6 Luna leads Nemotron 3 Ultra on coding, 58.0 to 30.0 on the Vibe Coding Index, and GPT-5.6 Luna costs 2.0x less per output token ($1.20 vs $2.40 per million). Updated October 22, 2026; 66 benchmarks have a result for both.
GPT-5.6 Luna or Nemotron 3 Ultra: which to pick
Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 30.0 for Nemotron 3 Ultra.
Pick Nemotron 3 Ultra for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 66
- GPT-5.6 Luna only
- 54
- Nemotron 3 Ultra only
- 5
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
GPT-5.6 Luna
GPT-5.6 Luna scores 58.0 against 30.0.
6 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 22.9.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 42.1 against 20.1.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Luna
GPT-5.6 Luna leads, 91.7% against 86.1%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.6 Luna
GPT-5.6 Luna leads, 86.0% against 85.8%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.6 Luna
GPT-5.6 Luna leads, 1255 against 1145.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.6 Luna
GPT-5.6 Luna $0.0008, Nemotron 3 Ultra $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Luna has the number, $0.04.
Directional only
At a glance
- Coding index
- GPT-5.6 Luna 58.0 from 6 benchmarks, Nemotron 3 Ultra 30.0 from 3 benchmarks.
- Widest category
- Agentic work, 23.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5.6 Luna 77.1% against Nemotron 3 Ultra 7.6%, 69.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Luna $1.20 against Nemotron 3 Ultra $2.40 per million output tokens, 2.0x apart.
- Context window
- GPT-5.6 Luna takes 1.05M tokens, Nemotron 3 Ultra 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5.6 Luna | Bars | Nemotron 3 Ultra | Ties |
|---|---|---|---|---|
| Coding | 8 | 2 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 5 | 0 | ||
| Reasoning | 7 | 1 | ||
| Math | 4 | 0 | ||
| Knowledge | 5 | 4 | ||
| Web design | 7 | 1 | ||
| General | 9 | 10 | ||
| All shared boards | 47 | 18 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index82
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev | 1518 | Not measured | Only GPT-5.6 Luna measured |
| AA Coding Index | 71.4 | 49.3 | GPT-5.6 Luna |
| LiveCodeBench (Vals AI) | Not measured | 86.0% | Only Nemotron 3 Ultra measured |
| SWE-bench Verified (Vals AI) | 93.0% | 69.0% | GPT-5.6 Luna |
| Terminal-Bench 4 (Vals AI) | 11.6% | Not measured | Only GPT-5.6 Luna measured |
| Vibe Code Bench (Vals AI) | 77.1% | 7.6% | GPT-5.6 Luna |
| Code migration (Vals AI) | 44.5% | 4.9% | GPT-5.6 Luna |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | 61.8% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 79.0% | 50.9% | GPT-5.6 Luna |
| Vibe Code Bench 1-100 (Vals AI) | 22.6% | Not measured | Only GPT-5.6 Luna measured |
| SkillsBench (Vals AI) | 60.5% | Not measured | Only GPT-5.6 Luna measured |
| CyberBench (Vals AI) | 73.6% | Not measured | Only GPT-5.6 Luna measured |
| SciCode | 53.6% | 40.3% | GPT-5.6 Luna |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 36.4% | Only Nemotron 3 Ultra measured |
| FrontierCode | 39.8% | 13.6% | GPT-5.6 Luna |
| WeirdML | 60.9% | 43.5% | GPT-5.6 Luna |
| ALE-Bench | 1667.4 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: coding | 1466 | 1468 | Nemotron 3 Ultra |
| LMArena Text: software and IT | 1463 | 1468 | Nemotron 3 Ultra |
| LMArena WebDev: React | 1508 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: HTML | 1520 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: from an image | 1517 | Not measured | Only GPT-5.6 Luna measured |
| SciCode | 6.2% | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| AA Intelligence Index | 37.3 | 22.9 | GPT-5.6 Luna |
| Epoch Capabilities Index | 156.5 | 146.0 | GPT-5.6 Luna |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| AA Agentic Index | 42.1 | 20.1 | GPT-5.6 Luna |
| LiveBench research | 51.0% | Not measured | Only GPT-5.6 Luna measured |
| LiveBench browser | 68.0% | Not measured | Only GPT-5.6 Luna measured |
| LiveBench long agentic | 30.4% | Not measured | Only GPT-5.6 Luna measured |
| SREBench (Vals AI) | 1.5% | Not measured | Only GPT-5.6 Luna measured |
| Finance Agent (Vals AI) | 55.0% | 37.7% | GPT-5.6 Luna |
| Tax Agent Bench (Vals AI) | 24.8% | Not measured | Only GPT-5.6 Luna measured |
| Legal Research Bench (Vals AI) | 36.5% | 15.4% | GPT-5.6 Luna |
| Excel Modeling Benchmark (Vals AI) | 67.1% | 31.7% | GPT-5.6 Luna |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only GPT-5.6 Luna measured |
| Vals Science Index | 25.3% | Not measured | Only GPT-5.6 Luna measured |
| τ²-Bench Telecom | Not measured | 83.3% | Only Nemotron 3 Ultra measured |
| APEX-Agents | 43.0% | 22.7% | GPT-5.6 Luna |
| BALROG | 45.6% | Not measured | Only GPT-5.6 Luna measured |
| Vending-Bench 2 | $4,095 | Not measured | Only GPT-5.6 Luna measured |
| MCP Atlas | Not measured | 63.1% | Only Nemotron 3 Ultra measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | 86.1% | GPT-5.6 Luna |
| LiveBench reasoning | 85.6% | Not measured | Only GPT-5.6 Luna measured |
| MysteryMechanism (Vals AI) | 14.4% | Not measured | Only GPT-5.6 Luna measured |
| MMMU Pro (Vals AI) | 85.0% | Not measured | Only GPT-5.6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | 91.1% | 86.7% | GPT-5.6 Luna |
| Humanity's Last Exam (Artificial Analysis run) | 39.5% | 28.4% | GPT-5.6 Luna |
| GPQA Diamond (Epoch AI run) | 91.6% | 85.4% | GPT-5.6 Luna |
| ARC-AGI | 88.0% | Not measured | Only GPT-5.6 Luna measured |
| ARC-AGI-2 | 59.5% | Not measured | Only GPT-5.6 Luna measured |
| SimpleBench | 46.8% | Not measured | Only GPT-5.6 Luna measured |
| Chess puzzles | 43.0% | Not measured | Only GPT-5.6 Luna measured |
| Mystery game puzzles | 21.0% | 20.0% | GPT-5.6 Luna |
| LMArena Text: hard prompts | 1451 | 1452 | Nemotron 3 Ultra |
| LMArena Text: expert | 1478 | 1472 | GPT-5.6 Luna |
| LMArena Text: hard prompts in English | 1460 | 1453 | GPT-5.6 Luna |
| LMArena Vision: diagrams | 1273 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: homework | 1282 | Not measured | Only GPT-5.6 Luna measured |
| Kagi LLM Benchmark | 49.1% | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 86.7% | GPT-5.6 Luna |
| FrontierMath, tiers 1 to 3 | 82.1% | Not measured | Only GPT-5.6 Luna measured |
| FrontierMath, tier 4 | 61.0% | Not measured | Only GPT-5.6 Luna measured |
| ProofBench | 60.0% | 2.0% | GPT-5.6 Luna |
| LMArena Text: math | 1459 | 1457 | GPT-5.6 Luna |
| LMArena Text: mathematical work | 1470 | 1461 | GPT-5.6 Luna |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index54
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| MMLU Pro | 86.0% | 85.8% | GPT-5.6 Luna |
| LegalBench (Vals AI) | 84.0% | 82.1% | GPT-5.6 Luna |
| CorpFin (Vals AI) | 64.2% | 65.5% | Nemotron 3 Ultra |
| TaxEval (Vals AI) | 76.2% | 73.1% | GPT-5.6 Luna |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Luna measured |
| MedCode (Vals AI) | 42.4% | 38.6% | GPT-5.6 Luna |
| SimpleQA Verified | 41.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: science | 1433 | 1465 | Nemotron 3 Ultra |
| LMArena Text: medicine and healthcare | 1399 | 1456 | Nemotron 3 Ultra |
| LMArena Text: legal and government | 1446 | 1452 | Nemotron 3 Ultra |
| LMArena Text: business and finance | 1439 | 1434 | GPT-5.6 Luna |
| FACTS Benchmark Suite | 35.0% | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| Design Arena: websites | 1255 | 1145 | GPT-5.6 Luna |
| Design Arena: UI components | 1248 | 1135 | GPT-5.6 Luna |
| Design Arena: game dev | 1195 | 1138 | GPT-5.6 Luna |
| Design Arena: data viz | 1212 | 1141 | GPT-5.6 Luna |
| Design Arena: 3D | 1121 | 1131 | Nemotron 3 Ultra |
| Design Arena: all code categories | 1230 | 1146 | GPT-5.6 Luna |
| Design Arena: SVG | 1193 | 1069 | GPT-5.6 Luna |
| Design Arena: ASCII art | 1142 | 1100 | GPT-5.6 Luna |
| LiveBench design | 76.0% | Not measured | Only GPT-5.6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index910
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| LiveBench data analysis | 78.0% | Not measured | Only GPT-5.6 Luna measured |
| Public Benefits Bench (Vals AI) | 61.2% | Not measured | Only GPT-5.6 Luna measured |
| SAGE (Vals AI) | 44.2% | Not measured | Only GPT-5.6 Luna measured |
| MedScribe (Vals AI) | 84.4% | Not measured | Only GPT-5.6 Luna measured |
| Vals Multimodal Index | 69.1% | Not measured | Only GPT-5.6 Luna measured |
| IFBench | Not measured | 81.4% | Only Nemotron 3 Ultra measured |
| Long context reasoning (AA-LCR) | 83.7% | 79.3% | GPT-5.6 Luna |
| DTBench | 89.1% | 90.1% | Nemotron 3 Ultra |
| LMCA | 48.5% | 36.9% | GPT-5.6 Luna |
| Surface Evolver Bench | 61.9% | Not measured | Only GPT-5.6 Luna measured |
| Furniture assembly | 42.5% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text | 1431 | 1445 | Nemotron 3 Ultra |
| LMArena Text: instruction following | 1437 | 1418 | GPT-5.6 Luna |
| LMArena Text: creative writing | 1396 | 1399 | Nemotron 3 Ultra |
| LMArena Vision | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: English | 1441 | 1455 | Nemotron 3 Ultra |
| LMArena Text: non-English | 1417 | 1427 | Nemotron 3 Ultra |
| LMArena Text: Chinese | 1470 | 1497 | Nemotron 3 Ultra |
| LMArena Text: German | 1455 | 1472 | Nemotron 3 Ultra |
| LMArena Text: Japanese | 1415 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Korean | 1415 | 1384 | GPT-5.6 Luna |
| LMArena Text: French | 1458 | 1472 | Nemotron 3 Ultra |
| LMArena Text: Spanish | 1446 | 1455 | Nemotron 3 Ultra |
| LMArena Text: Russian | 1427 | 1417 | GPT-5.6 Luna |
| LMArena Text: Polish | 1405 | 1385 | GPT-5.6 Luna |
| LMArena Text: multi-turn | 1434 | 1411 | GPT-5.6 Luna |
| LMArena Text: longer queries | 1436 | 1437 | Nemotron 3 Ultra |
| LMArena Text: writing and language | 1419 | 1406 | GPT-5.6 Luna |
| LMArena Text: entertainment and media | 1402 | 1397 | GPT-5.6 Luna |
| LMArena Vision: English | 1263 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: Chinese | 1294 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: reading text | 1264 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: humor | 1190 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: creative writing | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Document | 1457 | Not measured | Only GPT-5.6 Luna measured |
| EQ-Bench 4 | 1156 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Luna | Nemotron 3 Ultra | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GPT-5.6 Luna costs less
Repository review
50K input + 3K output tokens
GPT-5.6 Luna costs less
Agent loop
200K input + 10K output tokens
GPT-5.6 Luna costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.6 Luna | NVIDIA Nemotron 3 Ultra |
|---|---|---|
| Maker | OpenAI | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | June 4, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.20 | $0.60 |
| Output $/Mtok | $1.20 | $2.40 |
| Coding index | 58.0 | 30.0 |
| Independent measurements behind it | 6 | 3 |
| Cost per solved task | $0.04 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Luna better than Nemotron 3 Ultra for coding?
Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 30.0 for Nemotron 3 Ultra. Pick Nemotron 3 Ultra for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, GPT-5.6 Luna or Nemotron 3 Ultra?
GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens; Nemotron 3 Ultra costs $0.60 and $2.40. Cost per solved task is known for GPT-5.6 Luna only.
Which has the bigger context window, GPT-5.6 Luna or Nemotron 3 Ultra?
GPT-5.6 Luna, with 1.05M tokens against 262K.
How many benchmarks is the GPT-5.6 Luna vs Nemotron 3 Ultra comparison based on?
66 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Luna's coding index rests on 6 independent benchmarks and Nemotron 3 Ultra's on 3. Where only one model has a result, the page says so instead of naming a winner.