GPT-5.5 vs GPT-6 Luna
Updated October 21, 2026. 91 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-6 Luna for coding: it scores 71.4 on the Vibe Coding Index against 67.8 for GPT-5.5.
Pick GPT-5.5 when what matters is LiveBench coding or Code migration (Vals AI), where it leads.
- Shared results
- 91
- GPT-5.5 only
- 41
- GPT-6 Luna only
- 11
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
GPT-6 Luna
GPT-6 Luna scores 71.4 against 67.8.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 38.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.5 has a AA Agentic Index result, 36.4.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.5 has a GPQA Diamond result, 93.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.5 has a MMLU Pro result, 88.1%.
Directional only
Web design
Design Arena: websites
GPT-6 Luna
GPT-6 Luna leads, 1272 against 1256.
Same board, both measured
General
Vals Index
No call
Only GPT-6 Luna has a Vals Index result, 52.3%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Luna
GPT-5.5 $0.020, GPT-6 Luna $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.5 has the number, $1.65.
Directional only
At a glance
- Coding index
- GPT-5.5 67.8 from 2 benchmarks, GPT-6 Luna 71.4 from 2 benchmarks.
- Widest category
- Reasoning, 15.6 points apart on average over 12 shared benchmarks.
- Widest single gap
- Mystery game puzzles: GPT-5.5 56.0% against GPT-6 Luna 7.0%, 49.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 $30.00 against GPT-6 Luna $0.50 per million output tokens, 60.0x apart.
- Context window
- Both take 1.05M tokens.
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-5.5 | Bars | GPT-6 Luna | Ties |
|---|---|---|---|---|
| Coding | 8 | 5 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 7 | 5 | ||
| Reasoning | 12 | 0 | ||
| Math | 4 | 2 | ||
| Knowledge | 6 | 0 | ||
| Web design | 3 | 6 | ||
| General | 29 | 0 | 1 tie | |
| All shared boards | 71 | 18 | 2 ties |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index85
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| LiveBench coding | 85.1% | 84.5% | GPT-5.5 |
| LMArena WebDev | 1513 | 1578 | GPT-6 Luna |
| AA Coding Index | 74.9 | Not measured | Only GPT-5.5 measured |
| LiveCodeBench (Vals AI) | 85.3% | Not measured | Only GPT-5.5 measured |
| SWE-bench Verified (Vals AI) | 82.6% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 13.6% | Only GPT-6 Luna measured |
| Vibe Code Bench (Vals AI) | 69.8% | 81.7% | GPT-6 Luna |
| Code migration (Vals AI) | 45.2% | 42.5% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.5% | 0.5% | Tie |
| IOI (Vals AI) | Not measured | 55.6% | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 76.4% | 73.0% | GPT-5.5 |
| SWE-bench Multimodal (Vals AI) | Not measured | 37.5% | Only GPT-6 Luna measured |
| SkillsBench (Vals AI) | 62.5% | Not measured | Only GPT-5.5 measured |
| CyberBench (Vals AI) | Not measured | 76.3% | Only GPT-6 Luna measured |
| SciCode | 56.1% | 54.6% | GPT-5.5 |
| Terminal-Bench Hard (Artificial Analysis run) | 60.6% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench | 84.7% | Not measured | Only GPT-5.5 measured |
| FrontierCode | 43.0% | 42.4% | GPT-5.5 |
| GSO-Bench | 40.2% | Not measured | Only GPT-5.5 measured |
| WeirdML | 84.9% | Not measured | Only GPT-5.5 measured |
| MirrorCode | 10.0% | Not measured | Only GPT-5.5 measured |
| ALE-Bench | 1943.0 | 1576.9 | GPT-5.5 |
| LMArena Text: coding | 1494 | 1437 | GPT-5.5 |
| LMArena Text: software and IT | 1493 | 1423 | GPT-5.5 |
| LMArena WebDev: React | 1506 | 1573 | GPT-6 Luna |
| LMArena WebDev: HTML | 1543 | 1595 | GPT-6 Luna |
| LMArena WebDev: from an image | 1532 | 1571 | GPT-6 Luna |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 38.1 | GPT-5.5 |
| Epoch Capabilities Index | 159.7 | 156.8 | GPT-5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index75
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| AA Agentic Index | 36.4 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building web apps | 1117 | 1189 | GPT-6 Luna |
| Design Arena: agents building full-stack apps | 1089 | 1158 | GPT-6 Luna |
| Design Arena: agents building mobile apps | 1143 | 1133 | GPT-5.5 |
| Design Arena: agents building Android apps | 1169 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building Godot games | 1173 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building games | 1179 | Not measured | Only GPT-5.5 measured |
| Design Arena: HTML slides | 1067 | Not measured | Only GPT-5.5 measured |
| Design Arena: PowerPoint slides | 1108 | Not measured | Only GPT-5.5 measured |
| LiveBench research | 61.6% | 43.5% | GPT-5.5 |
| LiveBench browser | 48.0% | 72.0% | GPT-6 Luna |
| LiveBench long agentic | 44.6% | 48.1% | GPT-6 Luna |
| SREBench (Vals AI) | 3.8% | 2.7% | GPT-5.5 |
| Finance Agent (Vals AI) | 51.8% | 49.9% | GPT-5.5 |
| Tax Agent Bench (Vals AI) | 21.8% | 19.9% | GPT-5.5 |
| Legal Research Bench (Vals AI) | 40.4% | 30.3% | GPT-5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 4.2% | Only GPT-6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | 64.5% | 68.5% | GPT-6 Luna |
| BioMysteryBench (Vals AI) | Not measured | 61.5% | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 4.3% | Only GPT-6 Luna measured |
| Vals Science Index | Not measured | 28.4% | Only GPT-6 Luna measured |
| Time Horizon Index (Vals AI) | 8.3% | Not measured | Only GPT-5.5 measured |
| τ²-Bench Telecom | 93.9% | Not measured | Only GPT-5.5 measured |
| APEX-Agents | 55.1% | 44.3% | GPT-5.5 |
| Remote Labor Index | 6.3% | Not measured | Only GPT-5.5 measured |
| OSWorld 2.0 | 13.0% | Not measured | Only GPT-5.5 measured |
| DeepResearch Bench | 54.0% | Not measured | Only GPT-5.5 measured |
| PostTrainBench | 27.2% | Not measured | Only GPT-5.5 measured |
| SpireClimb | Not measured | 0.0% | Only GPT-6 Luna measured |
| Vending-Bench 2 | $7,524 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 9 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index120
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | Not measured | Only GPT-5.5 measured |
| LiveBench reasoning | 89.7% | 81.8% | GPT-5.5 |
| MysteryMechanism (Vals AI) | Not measured | 19.4% | Only GPT-6 Luna measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only GPT-5.5 measured |
| GPQA Diamond (Artificial Analysis run) | 93.5% | Not measured | Only GPT-5.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 45.8% | 38.5% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 90.7% | 90.5% | GPT-5.5 |
| ARC-AGI | 95.0% | 86.7% | GPT-5.5 |
| ARC-AGI-2 | 85.0% | 59.3% | GPT-5.5 |
| SimpleBench | 69.0% | Not measured | Only GPT-5.5 measured |
| Chess puzzles | 63.0% | 36.0% | GPT-5.5 |
| Mystery game puzzles | 56.0% | 7.0% | GPT-5.5 |
| EBR-bench | 34.3% | Not measured | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1489 | 1410 | GPT-5.5 |
| LMArena Text: expert | 1507 | 1442 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1483 | 1410 | GPT-5.5 |
| LMArena Vision: diagrams | 1325 | 1245 | GPT-5.5 |
| LMArena Vision: homework | 1332 | 1261 | GPT-5.5 |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index42
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| OTIS Mock AIME | 84.4% | 98.9% | GPT-6 Luna |
| FrontierMath, tiers 1 to 3 | 85.3% | 78.9% | GPT-5.5 |
| FrontierMath, tier 4 | 72.5% | 56.1% | GPT-5.5 |
| ProofBench | 50.0% | 64.0% | GPT-6 Luna |
| LMArena Text: math | 1487 | 1409 | GPT-5.5 |
| LMArena Text: mathematical work | 1496 | 1427 | GPT-5.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| MMLU Pro | 88.1% | Not measured | Only GPT-5.5 measured |
| LegalBench (Vals AI) | 86.5% | Not measured | Only GPT-5.5 measured |
| CaseLaw (Vals AI) | 66.2% | Not measured | Only GPT-5.5 measured |
| CorpFin (Vals AI) | 68.4% | Not measured | Only GPT-5.5 measured |
| TaxEval (Vals AI) | 75.0% | Not measured | Only GPT-5.5 measured |
| MortgageTax (Vals AI) | 68.8% | Not measured | Only GPT-5.5 measured |
| MedCode (Vals AI) | 49.1% | 44.7% | GPT-5.5 |
| SimpleQA Verified | 63.0% | 41.4% | GPT-5.5 |
| LMArena Text: science | 1485 | 1386 | GPT-5.5 |
| LMArena Text: medicine and healthcare | 1465 | 1352 | GPT-5.5 |
| LMArena Text: legal and government | 1491 | 1400 | GPT-5.5 |
| LMArena Text: business and finance | 1478 | 1388 | GPT-5.5 |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index36
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | 1272 | GPT-6 Luna |
| Design Arena: UI components | 1260 | 1297 | GPT-6 Luna |
| Design Arena: game dev | 1294 | 1259 | GPT-5.5 |
| Design Arena: data viz | 1265 | 1215 | GPT-5.5 |
| Design Arena: 3D | 1198 | 1217 | GPT-6 Luna |
| Design Arena: all code categories | 1260 | 1271 | GPT-6 Luna |
| Design Arena: SVG | 1234 | 1253 | GPT-6 Luna |
| Design Arena: ASCII art | 1254 | 1156 | GPT-5.5 |
| LiveBench design | 70.3% | 82.5% | GPT-6 Luna |
GeneralLike-for-likePublic boards, shown as published, kept out of the index290
| Benchmark | GPT-5.5 | GPT-6 Luna | Leader |
|---|---|---|---|
| Vals Index | Not measured | 52.3% | Only GPT-6 Luna measured |
| LiveBench data analysis | 81.6% | 73.4% | GPT-5.5 |
| Public Benefits Bench (Vals AI) | 60.9% | 57.6% | GPT-5.5 |
| SAGE (Vals AI) | 51.5% | 48.1% | GPT-5.5 |
| MedScribe (Vals AI) | 86.9% | 83.7% | GPT-5.5 |
| Vals Multimodal Index | 68.1% | Not measured | Only GPT-5.5 measured |
| IFBench | 75.9% | Not measured | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 84.3% | 83.3% | GPT-5.5 |
| DTBench | 96.0% | 90.1% | GPT-5.5 |
| LMCA | 54.3% | 44.5% | GPT-5.5 |
| Surface Evolver Bench | 88.1% | Not measured | Only GPT-5.5 measured |
| Furniture assembly | 44.2% | 44.2% | Tie |
| ExploitBench | 47.4% | Not measured | Only GPT-5.5 measured |
| CL-bench Life | 22.2% | Not measured | Only GPT-5.5 measured |
| LMArena Text | 1471 | 1389 | GPT-5.5 |
| LMArena Text: instruction following | 1478 | 1408 | GPT-5.5 |
| LMArena Text: creative writing | 1455 | 1363 | GPT-5.5 |
| LMArena Vision | 1297 | 1216 | GPT-5.5 |
| LMArena Text: English | 1470 | 1393 | GPT-5.5 |
| LMArena Text: non-English | 1467 | 1381 | GPT-5.5 |
| LMArena Text: Chinese | 1534 | 1427 | GPT-5.5 |
| LMArena Text: German | 1480 | 1376 | GPT-5.5 |
| LMArena Text: Japanese | 1499 | 1369 | GPT-5.5 |
| LMArena Text: Korean | 1460 | 1359 | GPT-5.5 |
| LMArena Text: French | 1485 | 1408 | GPT-5.5 |
| LMArena Text: Spanish | 1468 | 1391 | GPT-5.5 |
| LMArena Text: Russian | 1473 | 1392 | GPT-5.5 |
| LMArena Text: Polish | 1465 | 1383 | GPT-5.5 |
| LMArena Text: multi-turn | 1476 | 1392 | GPT-5.5 |
| LMArena Text: longer queries | 1484 | 1408 | GPT-5.5 |
| LMArena Text: writing and language | 1466 | 1384 | GPT-5.5 |
| LMArena Text: entertainment and media | 1449 | 1364 | GPT-5.5 |
| LMArena Vision: English | 1292 | 1204 | GPT-5.5 |
| LMArena Vision: Chinese | 1360 | 1266 | GPT-5.5 |
| LMArena Vision: reading text | 1306 | 1225 | GPT-5.5 |
| LMArena Vision: humor | 1293 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: recognizing things | 1231 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: creative writing | 1301 | 1205 | GPT-5.5 |
| LMArena Document | 1486 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 7 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 | GPT-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-6 Luna costs less
Repository review
50K input + 3K output tokens
GPT-6 Luna costs less
Agent loop
200K input + 10K output tokens
GPT-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-5.5 | OpenAI GPT-6 Luna |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 24, 2026 | September 22, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $5.00 | $0.10 |
| Output $/Mtok | $30.00 | $0.50 |
| Coding index | 67.8 | 71.4 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $1.65 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 better than GPT-6 Luna for coding?
Pick GPT-6 Luna for coding: it scores 71.4 on the Vibe Coding Index against 67.8 for GPT-5.5. Pick GPT-5.5 when what matters is LiveBench coding or Code migration (Vals AI), where it leads.
Which is cheaper, GPT-5.5 or GPT-6 Luna?
GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; GPT-6 Luna costs $0.10 and $0.50. Cost per solved task is known for GPT-5.5 only.
Which has the bigger context window, GPT-5.5 or GPT-6 Luna?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-5.5 vs GPT-6 Luna comparison based on?
91 benchmarks have a result for both models as of October 21, 2026. GPT-5.5's coding index rests on 2 independent benchmarks and GPT-6 Luna's on 2. Where only one model has a result, the page says so instead of naming a winner.