Nova Pro 1.0 vs GPT-5.6 Luna
GPT-5.6 Luna leads Nova Pro 1.0 on the Artificial Analysis Intelligence Index, 37.3 to 7.0, and GPT-5.6 Luna costs 2.7x less per output token ($1.20 vs $3.20 per million). Updated October 22, 2026; 34 benchmarks have a result for both.
Nova Pro 1.0 or GPT-5.6 Luna: which to pick
Only GPT-5.6 Luna has a coding score, 58.0 on the Vibe Coding Index; Nova Pro 1.0 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 34
- Nova Pro 1.0 only
- 8
- GPT-5.6 Luna only
- 85
- Like-for-like categories
- 7 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-5.6 Luna has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 7.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Luna has a AA Agentic Index result, 42.1.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Luna has a GPQA Diamond result, 91.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Luna has a MMLU Pro result, 86.0%.
Directional only
Web design
Design Arena: websites
GPT-5.6 Luna
GPT-5.6 Luna leads, 1255 against 796.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 300K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.6 Luna
Nova Pro 1.0 $0.0024, GPT-5.6 Luna $0.0008 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
- Nova Pro 1.0 not benchmarked, GPT-5.6 Luna 58.0 from 6 benchmarks.
- Widest category
- Web design, 57.4 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Nova Pro 1.0 21.0% against GPT-5.6 Luna 83.7%, 62.7 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against GPT-5.6 Luna $1.20 per million output tokens, 2.7x apart.
- Context window
- Nova Pro 1.0 takes 300K tokens, GPT-5.6 Luna 1.05M.
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 | Nova Pro 1.0 | Bars | GPT-5.6 Luna | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 1 | ||
| General | 0 | 19 | ||
| All shared boards | 0 | 34 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 73.6% | Only GPT-5.6 Luna measured |
| LMArena WebDev | Not measured | 1518 | Only GPT-5.6 Luna measured |
| AA Coding Index | Not measured | 71.4 | Only GPT-5.6 Luna measured |
| SWE-bench Verified (Vals AI) | Not measured | 93.0% | Only GPT-5.6 Luna measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 11.6% | Only GPT-5.6 Luna measured |
| Vibe Code Bench (Vals AI) | Not measured | 77.1% | Only GPT-5.6 Luna measured |
| Code migration (Vals AI) | Not measured | 44.5% | Only GPT-5.6 Luna measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only GPT-5.6 Luna measured |
| IOI (Vals AI) | Not measured | 61.8% | Only GPT-5.6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 79.0% | Only GPT-5.6 Luna measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 22.6% | Only GPT-5.6 Luna measured |
| SkillsBench (Vals AI) | Not measured | 60.5% | Only GPT-5.6 Luna measured |
| CyberBench (Vals AI) | Not measured | 73.6% | Only GPT-5.6 Luna measured |
| LiveCodeBench (Artificial Analysis run) | 23.3% | Not measured | Only Nova Pro 1.0 measured |
| SciCode | Not measured | 53.6% | Only GPT-5.6 Luna measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | Not measured | Only Nova Pro 1.0 measured |
| FrontierCode | Not measured | 39.8% | Only GPT-5.6 Luna measured |
| WeirdML | Not measured | 60.9% | Only GPT-5.6 Luna measured |
| ALE-Bench | Not measured | 1667.4 | Only GPT-5.6 Luna measured |
| LMArena Text: coding | 1270 | 1466 | GPT-5.6 Luna |
| LMArena Text: software and IT | 1271 | 1463 | GPT-5.6 Luna |
| LMArena WebDev: React | Not measured | 1508 | Only GPT-5.6 Luna measured |
| LMArena WebDev: HTML | Not measured | 1520 | Only GPT-5.6 Luna measured |
| LMArena WebDev: from an image | Not measured | 1517 | Only GPT-5.6 Luna measured |
| SciCode | Not measured | 6.2% | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 37.3 | GPT-5.6 Luna |
| Epoch Capabilities Index | Not measured | 156.5 | Only GPT-5.6 Luna measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 42.1 | Only GPT-5.6 Luna measured |
| LiveBench research | Not measured | 51.0% | Only GPT-5.6 Luna measured |
| LiveBench browser | Not measured | 68.0% | Only GPT-5.6 Luna measured |
| LiveBench long agentic | Not measured | 30.4% | Only GPT-5.6 Luna measured |
| SREBench (Vals AI) | Not measured | 1.5% | Only GPT-5.6 Luna measured |
| Finance Agent (Vals AI) | Not measured | 55.0% | Only GPT-5.6 Luna measured |
| Tax Agent Bench (Vals AI) | Not measured | 24.8% | Only GPT-5.6 Luna measured |
| Legal Research Bench (Vals AI) | Not measured | 36.5% | Only GPT-5.6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 67.1% | Only GPT-5.6 Luna measured |
| BioMysteryBench (Vals AI) | Not measured | 61.5% | Only GPT-5.6 Luna measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only GPT-5.6 Luna measured |
| Vals Science Index | Not measured | 25.3% | Only GPT-5.6 Luna measured |
| τ²-Bench Telecom | 14.0% | Not measured | Only Nova Pro 1.0 measured |
| APEX-Agents | Not measured | 43.0% | Only GPT-5.6 Luna measured |
| BALROG | Not measured | 45.6% | Only GPT-5.6 Luna measured |
| Vending-Bench 2 | Not measured | $4,095 | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 91.7% | Only GPT-5.6 Luna measured |
| LiveBench reasoning | Not measured | 85.6% | Only GPT-5.6 Luna measured |
| MysteryMechanism (Vals AI) | Not measured | 14.4% | Only GPT-5.6 Luna measured |
| MMMU Pro (Vals AI) | Not measured | 85.0% | Only GPT-5.6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | 49.9% | 91.1% | GPT-5.6 Luna |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 39.5% | GPT-5.6 Luna |
| GPQA Diamond (Epoch AI run) | Not measured | 91.6% | Only GPT-5.6 Luna measured |
| ARC-AGI | Not measured | 88.0% | Only GPT-5.6 Luna measured |
| ARC-AGI-2 | Not measured | 59.5% | Only GPT-5.6 Luna measured |
| SimpleBench | Not measured | 46.8% | Only GPT-5.6 Luna measured |
| Chess puzzles | Not measured | 43.0% | Only GPT-5.6 Luna measured |
| Mystery game puzzles | Not measured | 21.0% | Only GPT-5.6 Luna measured |
| LMArena Text: hard prompts | 1246 | 1451 | GPT-5.6 Luna |
| LMArena Text: expert | 1211 | 1478 | GPT-5.6 Luna |
| LMArena Text: hard prompts in English | 1259 | 1460 | GPT-5.6 Luna |
| LMArena Vision: diagrams | Not measured | 1273 | Only GPT-5.6 Luna measured |
| LMArena Vision: homework | Not measured | 1282 | Only GPT-5.6 Luna measured |
| Kagi LLM Benchmark | Not measured | 49.1% | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| AA Math Index | 7.0 | Not measured | Only Nova Pro 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 7.0% | Not measured | Only Nova Pro 1.0 measured |
| OTIS Mock AIME | Not measured | 98.3% | Only GPT-5.6 Luna measured |
| FrontierMath, tiers 1 to 3 | Not measured | 82.1% | Only GPT-5.6 Luna measured |
| FrontierMath, tier 4 | Not measured | 61.0% | Only GPT-5.6 Luna measured |
| ProofBench | Not measured | 60.0% | Only GPT-5.6 Luna measured |
| LMArena Text: math | 1252 | 1459 | GPT-5.6 Luna |
| LMArena Text: mathematical work | 1261 | 1470 | GPT-5.6 Luna |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.0% | Only GPT-5.6 Luna measured |
| LegalBench (Vals AI) | Not measured | 84.0% | Only GPT-5.6 Luna measured |
| CorpFin (Vals AI) | Not measured | 64.2% | Only GPT-5.6 Luna measured |
| TaxEval (Vals AI) | Not measured | 76.2% | Only GPT-5.6 Luna measured |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Luna measured |
| MedCode (Vals AI) | Not measured | 42.4% | Only GPT-5.6 Luna measured |
| MMLU Pro (Artificial Analysis run) | 69.1% | Not measured | Only Nova Pro 1.0 measured |
| SimpleQA Verified | Not measured | 41.0% | Only GPT-5.6 Luna measured |
| MMLU | 82.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: science | 1255 | 1433 | GPT-5.6 Luna |
| LMArena Text: medicine and healthcare | 1260 | 1399 | GPT-5.6 Luna |
| LMArena Text: legal and government | 1281 | 1446 | GPT-5.6 Luna |
| LMArena Text: business and finance | 1229 | 1439 | GPT-5.6 Luna |
| FACTS Benchmark Suite | Not measured | 35.0% | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| Design Arena: websites | 796 | 1255 | GPT-5.6 Luna |
| Design Arena: UI components | Not measured | 1248 | Only GPT-5.6 Luna measured |
| Design Arena: game dev | Not measured | 1194 | Only GPT-5.6 Luna measured |
| Design Arena: data viz | Not measured | 1211 | Only GPT-5.6 Luna measured |
| Design Arena: 3D | Not measured | 1121 | Only GPT-5.6 Luna measured |
| Design Arena: all code categories | Not measured | 1231 | Only GPT-5.6 Luna measured |
| Design Arena: SVG | Not measured | 1194 | Only GPT-5.6 Luna measured |
| Design Arena: ASCII art | Not measured | 1142 | Only GPT-5.6 Luna measured |
| LiveBench design | Not measured | 76.0% | Only GPT-5.6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 78.0% | Only GPT-5.6 Luna measured |
| Public Benefits Bench (Vals AI) | Not measured | 61.2% | Only GPT-5.6 Luna measured |
| SAGE (Vals AI) | Not measured | 44.2% | Only GPT-5.6 Luna measured |
| MedScribe (Vals AI) | Not measured | 84.4% | Only GPT-5.6 Luna measured |
| Vals Multimodal Index | Not measured | 69.1% | Only GPT-5.6 Luna measured |
| IFBench | 38.1% | Not measured | Only Nova Pro 1.0 measured |
| Long context reasoning (AA-LCR) | 21.0% | 83.7% | GPT-5.6 Luna |
| DTBench | Not measured | 89.1% | Only GPT-5.6 Luna measured |
| LMCA | Not measured | 48.5% | Only GPT-5.6 Luna measured |
| Surface Evolver Bench | Not measured | 61.9% | Only GPT-5.6 Luna measured |
| Furniture assembly | Not measured | 42.5% | Only GPT-5.6 Luna measured |
| LMArena Text | 1259 | 1431 | GPT-5.6 Luna |
| LMArena Text: instruction following | 1235 | 1437 | GPT-5.6 Luna |
| LMArena Text: creative writing | 1212 | 1396 | GPT-5.6 Luna |
| LMArena Vision | 980 | 1257 | GPT-5.6 Luna |
| LMArena Text: English | 1276 | 1441 | GPT-5.6 Luna |
| LMArena Text: non-English | 1233 | 1417 | GPT-5.6 Luna |
| LMArena Text: Chinese | 1244 | 1470 | GPT-5.6 Luna |
| LMArena Text: German | 1243 | 1455 | GPT-5.6 Luna |
| LMArena Text: Japanese | 1200 | 1415 | GPT-5.6 Luna |
| LMArena Text: Korean | 1203 | 1415 | GPT-5.6 Luna |
| LMArena Text: French | 1271 | 1458 | GPT-5.6 Luna |
| LMArena Text: Spanish | 1182 | 1446 | GPT-5.6 Luna |
| LMArena Text: Russian | 1240 | 1427 | GPT-5.6 Luna |
| LMArena Text: Polish | Not measured | 1405 | Only GPT-5.6 Luna measured |
| LMArena Text: multi-turn | 1246 | 1434 | GPT-5.6 Luna |
| LMArena Text: longer queries | 1255 | 1436 | GPT-5.6 Luna |
| LMArena Text: writing and language | 1247 | 1419 | GPT-5.6 Luna |
| LMArena Text: entertainment and media | 1210 | 1402 | GPT-5.6 Luna |
| LMArena Vision: English | 987 | 1263 | GPT-5.6 Luna |
| LMArena Vision: Chinese | Not measured | 1294 | Only GPT-5.6 Luna measured |
| LMArena Vision: reading text | Not measured | 1264 | Only GPT-5.6 Luna measured |
| LMArena Vision: humor | Not measured | 1190 | Only GPT-5.6 Luna measured |
| LMArena Vision: creative writing | Not measured | 1257 | Only GPT-5.6 Luna measured |
| LMArena Document | Not measured | 1457 | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Pro 1.0 | GPT-5.6 Luna | 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 | Amazon Nova Pro 1.0 | OpenAI GPT-5.6 Luna |
|---|---|---|
| Maker | Amazon | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | December 5, 2024 | July 9, 2026 |
| Context window | 300K | 1.05M |
| Input $/Mtok | $0.80 | $0.20 |
| Output $/Mtok | $3.20 | $1.20 |
| Coding index | Not benchmarked | 58.0 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | Not computable | $0.04 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Pro 1.0 better than GPT-5.6 Luna for coding?
Only GPT-5.6 Luna has a coding score, 58.0 on the Vibe Coding Index; Nova Pro 1.0 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Nova Pro 1.0 or GPT-5.6 Luna?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 per million output tokens; GPT-5.6 Luna costs $0.20 and $1.20. Cost per solved task is known for GPT-5.6 Luna only.
Which has the bigger context window, Nova Pro 1.0 or GPT-5.6 Luna?
GPT-5.6 Luna, with 1.05M tokens against 300K.
How many benchmarks is the Nova Pro 1.0 vs GPT-5.6 Luna comparison based on?
34 benchmarks have a result for both models as of October 22, 2026. Nova Pro 1.0's coding index rests on 0 independent benchmarks and GPT-5.6 Luna's on 6. Where only one model has a result, the page says so instead of naming a winner.