Claude Fable 5.2 vs GPT-6 Luna
Claude Fable 5.2 leads GPT-6 Luna on coding, 87.8 to 54.9 on the Vibe Coding Index, and GPT-6 Luna costs 80.0x less per output token ($0.50 vs $40.00 per million). Updated November 14, 2026; 60 benchmarks have a result for both.
vs boards won of 60 shared, 1 tied
Claude Fable 5.2 or GPT-6 Luna: which to pick
Pick Claude Fable 5.2 for coding: it scores 87.8 on the Vibe Coding Index against 54.9 for GPT-6 Luna, though on 4 benchmarks against 5.
Pick GPT-6 Luna for output tokens 80.0x cheaper ($0.50 vs $40.00 per million) and a larger context window (1.05M against 1M tokens).
Model AClaude Fable 5.2Anthropic87.8/1004 independent benchmarksNo cost per solved taskModel BGPT-6 LunaOpenAI54.9/1005 independent benchmarksNo cost per solved task
- Shared results
- 60
- Claude Fable 5.2 only
- 8
- GPT-6 Luna only
- 58
- 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
Claude Fable 5.2
Claude Fable 5.2 scores 87.8 against 54.9.
4 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Fable 5.2
Claude Fable 5.2 leads, 64.6 against 27.9.
Same board, both measured
Web design
Design Arena: websites
Claude Fable 5.2
Claude Fable 5.2 leads, 1351 against 1268.
Same board, both measured
General
Vals Index
Claude Fable 5.2
Claude Fable 5.2 leads, 71.3% against 52.3%.
Same board, both measured
Long documents
Listed context window
GPT-6 Luna
GPT-6 Luna takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Luna
Claude Fable 5.2 $0.028, GPT-6 Luna $0.0003 per turn.
List prices
At a glance
- Coding index
- Claude Fable 5.2 87.8 from 4 benchmarks, GPT-6 Luna 54.9 from 5 benchmarks.
- Widest category
- Reasoning, 37.1 points apart on average over 11 shared benchmarks.
- Widest single gap
- Mystery game puzzles: Claude Fable 5.2 90.0% against GPT-6 Luna 7.0%, 83.0 points apart on a 0 to 100 scale.
- Output price
- Claude Fable 5.2 $40.00 against GPT-6 Luna $0.50 per million output tokens, 80.0x apart.
- Context window
- Claude Fable 5.2 takes 1M tokens, GPT-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 | Claude Fable 5.2 | Bars | GPT-6 Luna | Ties |
|---|---|---|---|---|
| Coding | 13 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 14 | 0 | ||
| Reasoning | 11 | 0 | ||
| Math | 4 | 0 | ||
| Knowledge | 3 | 0 | ||
| Web design | 6 | 0 | ||
| General | 6 | 0 | 1 tie | |
| All shared boards | 59 | 0 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index130
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| LiveBench coding | 79.2% | 70.8% | Claude Fable 5.2 |
| LMArena WebDev | 1838 | 1577 | Claude Fable 5.2 |
| Terminal-Bench 4 (Vals AI) | 65.2% | 13.6% | Claude Fable 5.2 |
| Vibe Code Bench (Vals AI) | 93.8% | 81.7% | Claude Fable 5.2 |
| Code migration (Vals AI) | Not measured | 42.5% | Only GPT-6 Luna measured |
| ProgramBench (Vals AI) | 19.0% | 0.5% | Claude Fable 5.2 |
| IOI (Vals AI) | Not measured | 55.6% | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 73.0% | Only GPT-6 Luna measured |
| SWE-bench Multimodal (Vals AI) | 62.3% | 37.5% | Claude Fable 5.2 |
| CyberBench (Vals AI) | Not measured | 76.3% | Only GPT-6 Luna measured |
| SciCode | 67.7% | 54.6% | Claude Fable 5.2 |
| Terminal-Bench 4.0 (Artificial Analysis run) | 61.6% | 12.6% | Claude Fable 5.2 |
| FrontierCode 2.0 | 49.1% | 25.2% | Claude Fable 5.2 |
| FrontierCode | Not measured | 42.4% | Only GPT-6 Luna measured |
| FrontierSWE | 69.9% | Not measured | Only Claude Fable 5.2 measured |
| MirrorCode | Not measured | 26.7% | Only GPT-6 Luna measured |
| ALE-Bench | 2509.8 | 1576.9 | Claude Fable 5.2 |
| LMArena Text: coding | Not measured | 1431 | Only GPT-6 Luna measured |
| LMArena Text: software and IT | Not measured | 1422 | Only GPT-6 Luna measured |
| LMArena WebDev: React | 1915 | 1574 | Claude Fable 5.2 |
| LMArena WebDev: HTML | 1738 | 1595 | Claude Fable 5.2 |
| LMArena WebDev: from an image | Not measured | 1566 | Only GPT-6 Luna measured |
| GameBench 2 | 99.1 | 55.9 | Claude Fable 5.2 |
| Terminal-Bench 4.0 | Not measured | 16.4% | Only GPT-6 Luna measured |
| CursorBench 4.0 | 60.0% | Not measured | Only Claude Fable 5.2 measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| AA Intelligence Index | 64.6 | 27.9 | Claude Fable 5.2 |
| Epoch Capabilities Index | 173.4 | 156.4 | Claude Fable 5.2 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index140
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1150 | Only GPT-6 Luna measured |
| Design Arena: agents building full-stack apps | 1402 | 1138 | Claude Fable 5.2 |
| Design Arena: agents building mobile apps | 1325 | 1117 | Claude Fable 5.2 |
| Design Arena: agents building Android apps | Not measured | 1176 | Only GPT-6 Luna measured |
| Design Arena: spreadsheets | 1434 | 875 | Claude Fable 5.2 |
| LiveBench research | 94.5% | 48.5% | Claude Fable 5.2 |
| LiveBench browser | 86.9% | 70.3% | Claude Fable 5.2 |
| LiveBench long agentic | 82.9% | 24.7% | Claude Fable 5.2 |
| SREBench (Vals AI) | Not measured | 2.7% | Only GPT-6 Luna measured |
| Finance Agent (Vals AI) | Not measured | 49.9% | Only GPT-6 Luna measured |
| Tax Agent Bench (Vals AI) | 32.1% | 19.9% | Claude Fable 5.2 |
| Legal Research Bench (Vals AI) | 46.1% | 30.3% | Claude Fable 5.2 |
| Harvey's Legal Agent Benchmark (Vals AI) | 5.0% | 4.2% | Claude Fable 5.2 |
| Excel Modeling Benchmark (Vals AI) | Not measured | 68.5% | Only GPT-6 Luna measured |
| BioMysteryBench (Vals AI) | 83.7% | 61.5% | Claude Fable 5.2 |
| Terminal-Bench-Science (Vals AI) | 55.7% | 4.3% | Claude Fable 5.2 |
| Vals Science Index | 63.7% | 28.4% | Claude Fable 5.2 |
| APEX-Agents | 80.1% | 44.3% | Claude Fable 5.2 |
| Remote Labor Index | 41.3% | Not measured | Only Claude Fable 5.2 measured |
| SpireClimb | 15.5% | 0.0% | Claude Fable 5.2 |
| LMArena Search | Not measured | 1160 | 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 index110
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| LiveBench reasoning | 88.8% | 81.8% | Claude Fable 5.2 |
| MysteryMechanism (Vals AI) | 51.8% | 19.4% | Claude Fable 5.2 |
| Humanity's Last Exam (Artificial Analysis run) | 74.3% | 38.5% | Claude Fable 5.2 |
| HLE-Diamond (Artificial Analysis run) | 80.2% | 22.2% | Claude Fable 5.2 |
| CritPt v2, hard subset (Artificial Analysis run) | 76.5% | 42.5% | Claude Fable 5.2 |
| GPQA Diamond (Epoch AI run) | 93.9% | 90.5% | Claude Fable 5.2 |
| ARC-AGI | 98.5% | 86.7% | Claude Fable 5.2 |
| ARC-AGI-2 | 93.8% | 59.3% | Claude Fable 5.2 |
| SimpleBench | 94.9% | Not measured | Only Claude Fable 5.2 measured |
| Chess puzzles | 79.0% | 36.0% | Claude Fable 5.2 |
| Mystery game puzzles | 90.0% | 7.0% | Claude Fable 5.2 |
| EBR-bench | 90.5% | Not measured | Only Claude Fable 5.2 measured |
| LMArena Text: hard prompts | Not measured | 1407 | Only GPT-6 Luna measured |
| LMArena Text: expert | Not measured | 1437 | Only GPT-6 Luna measured |
| LMArena Text: hard prompts in English | Not measured | 1407 | Only GPT-6 Luna measured |
| LMArena Vision: diagrams | Not measured | 1235 | Only GPT-6 Luna measured |
| LMArena Vision: homework | Not measured | 1252 | Only GPT-6 Luna measured |
| Humanity's Last Exam (Scale run) | 72.4% | Not measured | Only Claude Fable 5.2 measured |
| GoBench | 2566 | 1120 | Claude Fable 5.2 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| OTIS Mock AIME | 99.7% | 98.9% | Claude Fable 5.2 |
| FrontierMath, tiers 1 to 3 | 95.1% | 78.9% | Claude Fable 5.2 |
| FrontierMath, tier 4 | 100.0% | 56.1% | Claude Fable 5.2 |
| ProofBench | 100.0% | 64.0% | Claude Fable 5.2 |
| LMArena Text: math | Not measured | 1411 | Only GPT-6 Luna measured |
| LMArena Text: mathematical work | Not measured | 1425 | Only GPT-6 Luna measured |
| MathArena | 82.8% | Not measured | Only Claude Fable 5.2 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 44.7% | Only GPT-6 Luna measured |
| AA-Omniscience | 66.8 | -8.3 | Claude Fable 5.2 |
| SimpleQA Verified | 94.0% | 41.4% | Claude Fable 5.2 |
| LMArena Text: science | Not measured | 1387 | Only GPT-6 Luna measured |
| LMArena Text: medicine and healthcare | Not measured | 1349 | Only GPT-6 Luna measured |
| LMArena Text: legal and government | Not measured | 1392 | Only GPT-6 Luna measured |
| LMArena Text: business and finance | Not measured | 1382 | Only GPT-6 Luna measured |
| FACTS Benchmark Suite | Not measured | 64.8% | Only GPT-6 Luna measured |
| PRBench Finance | 47.1% | Not measured | Only Claude Fable 5.2 measured |
| PRBench Legal | 49.0% | 42.9% | Claude Fable 5.2 |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| Design Arena: websites | 1351 | 1268 | Claude Fable 5.2 |
| Design Arena: UI components | 1371 | 1291 | Claude Fable 5.2 |
| Design Arena: game dev | 1396 | 1253 | Claude Fable 5.2 |
| Design Arena: data viz | Not measured | 1208 | Only GPT-6 Luna measured |
| Design Arena: 3D | 1517 | 1194 | Claude Fable 5.2 |
| Design Arena: all code categories | 1373 | 1261 | Claude Fable 5.2 |
| Design Arena: SVG | Not measured | 1235 | Only GPT-6 Luna measured |
| Design Arena: ASCII art | Not measured | 1161 | Only GPT-6 Luna measured |
| LiveBench design | 85.1% | 76.1% | Claude Fable 5.2 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Fable 5.2 | GPT-6 Luna | Leader |
|---|---|---|---|
| Vals Index | 71.3% | 52.3% | Claude Fable 5.2 |
| LiveBench data analysis | 81.5% | 73.4% | Claude Fable 5.2 |
| Public Benefits Bench (Vals AI) | Not measured | 57.6% | Only GPT-6 Luna measured |
| SAGE (Vals AI) | Not measured | 83.4% | Only GPT-6 Luna measured |
| MedScribe (Vals AI) | Not measured | 83.7% | Only GPT-6 Luna measured |
| Long context reasoning (AA-LCR) | 83.3% | 83.3% | Tie |
| GDPval-AA | 1831 | 1443 | Claude Fable 5.2 |
| DTBench | 99.2% | 90.1% | Claude Fable 5.2 |
| LMCA | 70.6% | 44.5% | Claude Fable 5.2 |
| Furniture assembly | 90.0% | 44.2% | Claude Fable 5.2 |
| LMArena Text | Not measured | 1388 | Only GPT-6 Luna measured |
| LMArena Text: instruction following | Not measured | 1403 | Only GPT-6 Luna measured |
| LMArena Text: creative writing | Not measured | 1359 | Only GPT-6 Luna measured |
| LMArena Vision | Not measured | 1211 | Only GPT-6 Luna measured |
| LMArena Text: English | Not measured | 1391 | Only GPT-6 Luna measured |
| LMArena Text: non-English | Not measured | 1380 | Only GPT-6 Luna measured |
| LMArena Text: Chinese | Not measured | 1422 | Only GPT-6 Luna measured |
| LMArena Text: German | Not measured | 1384 | Only GPT-6 Luna measured |
| LMArena Text: Japanese | Not measured | 1366 | Only GPT-6 Luna measured |
| LMArena Text: Korean | Not measured | 1347 | Only GPT-6 Luna measured |
| LMArena Text: French | Not measured | 1405 | Only GPT-6 Luna measured |
| LMArena Text: Spanish | Not measured | 1395 | Only GPT-6 Luna measured |
| LMArena Text: Russian | Not measured | 1388 | Only GPT-6 Luna measured |
| LMArena Text: Polish | Not measured | 1382 | Only GPT-6 Luna measured |
| LMArena Text: multi-turn | Not measured | 1393 | Only GPT-6 Luna measured |
| LMArena Text: longer queries | Not measured | 1403 | Only GPT-6 Luna measured |
| LMArena Text: writing and language | Not measured | 1382 | Only GPT-6 Luna measured |
| LMArena Text: entertainment and media | Not measured | 1359 | Only GPT-6 Luna measured |
| LMArena Vision: English | Not measured | 1204 | Only GPT-6 Luna measured |
| LMArena Vision: Chinese | Not measured | 1274 | Only GPT-6 Luna measured |
| LMArena Vision: reading text | Not measured | 1221 | Only GPT-6 Luna measured |
| LMArena Vision: humor | Not measured | 1168 | Only GPT-6 Luna measured |
| LMArena Vision: creative writing | Not measured | 1190 | 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 | Claude Fable 5.2 | 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
Claude Fable 5.2$0.028Fits in one request
GPT-6 Luna$0.0003Fits in one request
GPT-6 Luna costs less
Repository review
50K input + 3K output tokens
Claude Fable 5.2$0.520Fits in one request
GPT-6 Luna$0.0065Fits in one request
GPT-6 Luna costs less
Agent loop
200K input + 10K output tokens
Claude Fable 5.2$2.00Fits in one request
GPT-6 Luna$0.025Fits in one request
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 | Anthropic Claude Fable 5.2 | OpenAI GPT-6 Luna |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | November 9, 2026 | September 22, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $8.00 | $0.10 |
| Output $/Mtok | $40.00 | $0.50 |
| Coding index | 87.8 | 54.9 |
| Independent measurements behind it | 4 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Fable 5.2 better than GPT-6 Luna for coding?
Pick Claude Fable 5.2 for coding: it scores 87.8 on the Vibe Coding Index against 54.9 for GPT-6 Luna, though on 4 benchmarks against 5. Pick GPT-6 Luna for output tokens 80.0x cheaper ($0.50 vs $40.00 per million) and a larger context window (1.05M against 1M tokens).
Which is cheaper, Claude Fable 5.2 or GPT-6 Luna?
Claude Fable 5.2 costs $8.00 per million input tokens and $40.00 per million output tokens; GPT-6 Luna costs $0.10 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Claude Fable 5.2 or GPT-6 Luna?
GPT-6 Luna, with 1.05M tokens against 1M.
How many benchmarks is the Claude Fable 5.2 vs GPT-6 Luna comparison based on?
60 benchmarks have a result for both models as of November 14, 2026. Claude Fable 5.2's coding index rests on 4 independent benchmarks and GPT-6 Luna's on 5. Where only one model has a result, the page says so instead of naming a winner.