GPT-6 Luna vs Nemotron 3 Super
GPT-6 Luna leads Nemotron 3 Super on the Artificial Analysis Intelligence Index, 38.1 to 12.8, at about the same output price ($0.50 vs $0.45 per million). Updated October 22, 2026; 31 benchmarks have a result for both.
GPT-6 Luna or Nemotron 3 Super: which to pick
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; Nemotron 3 Super has none, so the two cannot be ranked on coding.
Pick Nemotron 3 Super for output tokens 1.1x cheaper ($0.45 vs $0.50 per million) and work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.
- Shared results
- 31
- GPT-6 Luna only
- 73
- Nemotron 3 Super only
- 8
- Like-for-like categories
- 6 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
No call
Only GPT-6 Luna has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Luna
GPT-6 Luna leads, 38.1 against 12.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Nemotron 3 Super has a AA Agentic Index result, 1.7.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6 Luna has a Design Arena: websites result, 1271.
Directional only
General
Vals Index
No call
Only GPT-6 Luna has a Vals Index result, 52.3%.
Directional only
Long documents
Listed context window
GPT-6 Luna
GPT-6 Luna takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3 Super
GPT-6 Luna $0.0003, Nemotron 3 Super $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-6 Luna 57.3 from 5 benchmarks, Nemotron 3 Super not benchmarked.
- Widest category
- Intelligence, 25.3 points apart on average over 1 shared benchmark.
- Widest single gap
- ALE-Bench: GPT-6 Luna 1576.9 against Nemotron 3 Super 213.9, 45.4 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Luna $0.50 against Nemotron 3 Super $0.45 per million output tokens, 1.1x apart.
- Context window
- GPT-6 Luna takes 1.05M tokens, Nemotron 3 Super 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-6 Luna | Bars | Nemotron 3 Super | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 2 | 2 | ||
| General | 13 | 3 | ||
| All shared boards | 26 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev | 1578 | Not measured | Only GPT-6 Luna measured |
| AA Coding Index | Not measured | 37.7 | Only Nemotron 3 Super measured |
| Terminal-Bench 4 (Vals AI) | 13.6% | Not measured | Only GPT-6 Luna measured |
| Vibe Code Bench (Vals AI) | 81.7% | Not measured | Only GPT-6 Luna measured |
| Code migration (Vals AI) | 42.5% | Not measured | Only GPT-6 Luna measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-6 Luna measured |
| IOI (Vals AI) | 55.6% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 73.0% | Not measured | Only GPT-6 Luna measured |
| SWE-bench Multimodal (Vals AI) | 37.5% | Not measured | Only GPT-6 Luna measured |
| CyberBench (Vals AI) | 76.3% | Not measured | Only GPT-6 Luna measured |
| SciCode | 54.6% | 36.2% | GPT-6 Luna |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 28.8% | Only Nemotron 3 Super measured |
| FrontierCode | 42.4% | Not measured | Only GPT-6 Luna measured |
| WeirdML | Not measured | 38.0% | Only Nemotron 3 Super measured |
| ALE-Bench | 1576.9 | 213.9 | GPT-6 Luna |
| LMArena Text: coding | 1437 | 1403 | GPT-6 Luna |
| LMArena Text: software and IT | 1423 | 1409 | GPT-6 Luna |
| LMArena WebDev: React | 1573 | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev: HTML | 1595 | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev: from an image | 1571 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.1 | 12.8 | GPT-6 Luna |
| Epoch Capabilities Index | 156.8 | Not measured | Only GPT-6 Luna measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.7 | Only Nemotron 3 Super measured |
| Design Arena: agents building web apps | 1191 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building full-stack apps | 1158 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building mobile apps | 1131 | Not measured | Only GPT-6 Luna measured |
| LiveBench research | 43.5% | Not measured | Only GPT-6 Luna measured |
| LiveBench browser | 72.0% | Not measured | Only GPT-6 Luna measured |
| LiveBench long agentic | 48.1% | Not measured | Only GPT-6 Luna measured |
| SREBench (Vals AI) | 2.7% | Not measured | Only GPT-6 Luna measured |
| Finance Agent (Vals AI) | 49.9% | Not measured | Only GPT-6 Luna measured |
| Tax Agent Bench (Vals AI) | 19.9% | Not measured | Only GPT-6 Luna measured |
| Legal Research Bench (Vals AI) | 30.3% | Not measured | Only GPT-6 Luna measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | Not measured | Only GPT-6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | 68.5% | Not measured | Only GPT-6 Luna measured |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only GPT-6 Luna measured |
| Vals Science Index | 28.4% | Not measured | Only GPT-6 Luna measured |
| τ²-Bench Telecom | Not measured | 67.8% | Only Nemotron 3 Super measured |
| APEX-Agents | 44.3% | Not measured | Only GPT-6 Luna measured |
| SpireClimb | 0.0% | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| LiveBench reasoning | 81.8% | Not measured | Only GPT-6 Luna measured |
| MysteryMechanism (Vals AI) | 19.4% | Not measured | Only GPT-6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.0% | Only Nemotron 3 Super measured |
| Humanity's Last Exam (Artificial Analysis run) | 38.5% | 20.8% | GPT-6 Luna |
| GPQA Diamond (Epoch AI run) | 90.5% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI | 86.7% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI-2 | 59.3% | Not measured | Only GPT-6 Luna measured |
| Chess puzzles | 36.0% | Not measured | Only GPT-6 Luna measured |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: hard prompts | 1410 | 1386 | GPT-6 Luna |
| LMArena Text: expert | 1442 | 1398 | GPT-6 Luna |
| LMArena Text: hard prompts in English | 1410 | 1397 | GPT-6 Luna |
| LMArena Vision: diagrams | 1245 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: homework | 1261 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tiers 1 to 3 | 78.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tier 4 | 56.1% | Not measured | Only GPT-6 Luna measured |
| ProofBench | 64.0% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: math | 1409 | 1380 | GPT-6 Luna |
| LMArena Text: mathematical work | 1427 | 1405 | GPT-6 Luna |
| MathArena | Not measured | 16.6% | Only Nemotron 3 Super measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 44.7% | Not measured | Only GPT-6 Luna measured |
| SimpleQA Verified | 41.4% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: science | 1386 | 1387 | Nemotron 3 Super |
| LMArena Text: medicine and healthcare | 1352 | 1383 | Nemotron 3 Super |
| LMArena Text: legal and government | 1400 | 1392 | GPT-6 Luna |
| LMArena Text: business and finance | 1388 | 1364 | GPT-6 Luna |
| FACTS Benchmark Suite | 63.3% | Not measured | Only GPT-6 Luna measured |
| PRBench Legal | 42.9% | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| Design Arena: websites | 1271 | Not measured | Only GPT-6 Luna measured |
| Design Arena: UI components | 1295 | Not measured | Only GPT-6 Luna measured |
| Design Arena: game dev | 1258 | Not measured | Only GPT-6 Luna measured |
| Design Arena: data viz | 1217 | Not measured | Only GPT-6 Luna measured |
| Design Arena: 3D | 1218 | Not measured | Only GPT-6 Luna measured |
| Design Arena: all code categories | 1270 | Not measured | Only GPT-6 Luna measured |
| Design Arena: SVG | 1253 | Not measured | Only GPT-6 Luna measured |
| Design Arena: ASCII art | 1153 | Not measured | Only GPT-6 Luna measured |
| LiveBench design | 82.5% | Not measured | Only GPT-6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index133
| Benchmark | GPT-6 Luna | Nemotron 3 Super | Leader |
|---|---|---|---|
| Vals Index | 52.3% | Not measured | Only GPT-6 Luna measured |
| LiveBench data analysis | 73.4% | Not measured | Only GPT-6 Luna measured |
| Public Benefits Bench (Vals AI) | 57.6% | Not measured | Only GPT-6 Luna measured |
| SAGE (Vals AI) | 48.1% | Not measured | Only GPT-6 Luna measured |
| MedScribe (Vals AI) | 83.7% | Not measured | Only GPT-6 Luna measured |
| IFBench | Not measured | 71.5% | Only Nemotron 3 Super measured |
| Long context reasoning (AA-LCR) | 83.3% | 65.7% | GPT-6 Luna |
| DTBench | 90.1% | Not measured | Only GPT-6 Luna measured |
| LMCA | 44.5% | Not measured | Only GPT-6 Luna measured |
| Furniture assembly | 44.2% | Not measured | Only GPT-6 Luna measured |
| LMArena Text | 1389 | 1378 | GPT-6 Luna |
| LMArena Text: instruction following | 1408 | 1347 | GPT-6 Luna |
| LMArena Text: creative writing | 1363 | 1317 | GPT-6 Luna |
| LMArena Vision | 1216 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: English | 1393 | 1400 | Nemotron 3 Super |
| LMArena Text: non-English | 1381 | 1356 | GPT-6 Luna |
| LMArena Text: Chinese | 1427 | 1431 | Nemotron 3 Super |
| LMArena Text: German | 1376 | 1341 | GPT-6 Luna |
| LMArena Text: Japanese | 1369 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Korean | 1359 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: French | 1408 | 1403 | GPT-6 Luna |
| LMArena Text: Spanish | 1391 | 1418 | Nemotron 3 Super |
| LMArena Text: Russian | 1392 | 1336 | GPT-6 Luna |
| LMArena Text: Polish | 1383 | 1346 | GPT-6 Luna |
| LMArena Text: multi-turn | 1392 | 1369 | GPT-6 Luna |
| LMArena Text: longer queries | 1408 | 1362 | GPT-6 Luna |
| LMArena Text: writing and language | 1384 | 1332 | GPT-6 Luna |
| LMArena Text: entertainment and media | 1364 | 1336 | GPT-6 Luna |
| LMArena Vision: English | 1204 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: Chinese | 1266 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: reading text | 1225 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: creative writing | 1205 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Luna | Nemotron 3 Super | 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
Nemotron 3 Super costs less
Repository review
50K input + 3K output tokens
Nemotron 3 Super costs less
Agent loop
200K input + 10K output tokens
Nemotron 3 Super 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-6 Luna | NVIDIA Nemotron 3 Super |
|---|---|---|
| Maker | OpenAI | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | September 22, 2026 | March 11, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.10 | $0.085 |
| Output $/Mtok | $0.50 | $0.45 |
| Coding index | 57.3 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Luna better than Nemotron 3 Super for coding?
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; Nemotron 3 Super has none, so the two cannot be ranked on coding. Pick Nemotron 3 Super for output tokens 1.1x cheaper ($0.45 vs $0.50 per million) and work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.
Which is cheaper, GPT-6 Luna or Nemotron 3 Super?
GPT-6 Luna costs $0.10 per million input tokens and $0.50 per million output tokens; Nemotron 3 Super costs $0.085 and $0.45. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Luna or Nemotron 3 Super?
GPT-6 Luna, with 1.05M tokens against 262K.
How many benchmarks is the GPT-6 Luna vs Nemotron 3 Super comparison based on?
31 benchmarks have a result for both models as of October 22, 2026. GPT-6 Luna's coding index rests on 5 independent benchmarks and Nemotron 3 Super's on 0. Where only one model has a result, the page says so instead of naming a winner.