Model comparison
Claude Fable 5 vs GPT-6 Luna
Claude Fable 5 is the stronger model overall, scoring 66.3 to 45.1 on the Noometry Index. GPT-6 Luna costs 100× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. Claude Fable 5 scores higher in 9 categories and GPT-6 Luna in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Fable 5 leads 88.4 to 35.6.
- The biggest single-benchmark swing is NYT Connections (extended): 92.7% for Claude Fable 5 and 68.7% for GPT-6 Luna.
- GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $10 / $50 for Claude Fable 5.
- GPT-6 Luna accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Fable 5 | GPT-6 Luna | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 66.3 | 45.1 |
| Released | 2026-06-07 | 2026-09-22 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $10 | $0.10 |
| Output $ / M tokens | $50 | $0.50 |
| Results tracked | 61 | 18 |
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Category by category
Coding Claude Fable 5 leads
Claude Fable 5: 67.0 (#4), GPT-6 Luna: 54.7 (#24)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| DeepSWE | 69.9% | 66.6% |
| FrontierCode | 53.5% | 42.4% |
| LMArena WebDev | 1626 | 1583 |
| LMArena Coding | 1519 | 1448 |
| FrontierSWE | 47% | — |
| SciCode | 61% | — |
| WeirdML | 91.9% | — |
| MirrorCode | 63.9% | — |
| ALE-Bench | 2,041 | — |
Agentic & Tool Use Not comparable
Claude Fable 5: 54.1 (#2), GPT-6 Luna: —
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| APEX-Agents | 63.6% | — |
| Remote Labor Index | 16.1% | — |
| τ²-bench Banking | 39.7% | — |
| PostTrainBench | 41.8% | — |
| GBAEval | 74.5% | — |
| GDP.pdf | 30% | — |
| LMArena Search | 1230 | — |
| Vending-Bench 2 | 5,680 | — |
Reasoning Claude Fable 5 leads
Claude Fable 5: 76.8 (#4), GPT-6 Luna: 31.7 (#68)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| NYT Connections (extended) | 92.7% | 68.7% |
| LMArena Hard Prompts | 1508 | 1415 |
| ARC-AGI-2 | 89.2% | — |
| SimpleBench | 81.9% | — |
| Kagi LLM Benchmark | 91.4% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 28.6% | — |
| Chess Puzzles | 41% | — |
| EnigmaEval | 39.3% | — |
| EBR-Bench | 39.5% | — |
| Mystery Game Puzzles | 52% | — |
| DTBench | 98.4% | — |
| LMCA | 61.1% | — |
| Surface Evolver Bench | 95% | — |
| Bench to the Future 3 | 0.13 | — |
| Epoch Capabilities Index | 163.6 | — |
Math Claude Fable 5 leads
Claude Fable 5: 88.4 (#5), GPT-6 Luna: 35.6 (#140)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| LMArena Math | 1519 | 1396 |
| FrontierMath (Tiers 1-3) | 87% | — |
| FrontierMath Tier 4 | 90.2% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 95% | — |
| FrontierMath Erdős | 0% | — |
Knowledge Claude Fable 5 leads
Claude Fable 5: 62.3 (#22), GPT-6 Luna: 40.1 (#110)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| LMArena Expert | 1534 | 1458 |
| GPQA Diamond | 85.9% | — |
| SimpleQA Verified | 70.7% | — |
Multimodal Claude Fable 5 leads
Claude Fable 5: 45.6 (#14), GPT-6 Luna: 42.0 (#27)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| Furniture Assembly | 35.8% | 44.2% |
| LMArena Vision | 1326 | — |
| Blueprint-Bench 2 | 38.6% | — |
| LMArena Document | 1496 | — |
Multilingual Claude Fable 5 leads
Claude Fable 5: 57.6 (#8), GPT-6 Luna: 51.0 (#111)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| LMArena Non-English | 1483 | 1390 |
| LMArena Chinese | 1546 | 1425 |
| LMArena Russian | 1507 | 1392 |
| LMArena Spanish | 1503 | 1416 |
| LMArena French | 1509 | — |
| LMArena German | 1486 | — |
| LMArena Japanese | 1507 | — |
| LMArena Korean | 1493 | — |
Instruction Following Claude Fable 5 leads
Claude Fable 5: 78.8 (#7), GPT-6 Luna: 74.7 (#85)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| LMArena Instruction Following | 1503 | 1414 |
Long Context Claude Fable 5 leads
Claude Fable 5: 46.3 (#22), GPT-6 Luna: 43.3 (#95)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| LMArena Longer Query | 1510 | 1417 |
Writing & Preference Claude Fable 5 leads
Claude Fable 5: 76.1 (#5), GPT-6 Luna: 58.4 (#115)
| Benchmark | Claude Fable 5 | GPT-6 Luna |
|---|---|---|
| LMArena Text | 1491 | 1392 |
| LMArena Creative Writing | 1494 | 1357 |
| LMArena Multi-Turn | 1505 | 1400 |
| EQ-Bench Creative Writing | 1943 | — |
| EQ-Bench 4 | 1340 | — |
Frequently asked questions
Is Claude Fable 5 better than GPT-6 Luna?
Claude Fable 5 is the stronger model overall, scoring 66.3 to 45.1 on the Noometry Index. GPT-6 Luna costs 100× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Which is cheaper, Claude Fable 5 or GPT-6 Luna?
GPT-6 Luna is cheaper. It lists at $0.10 per million input tokens and $0.50 per million output tokens; Claude Fable 5 lists at $10 and $50.
Is Claude Fable 5 or GPT-6 Luna better for coding?
Claude Fable 5 scores higher on coding benchmarks: 67.0 versus 54.7 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 1M.
How many benchmarks do Claude Fable 5 and GPT-6 Luna share?
18 benchmarks have published results for both models. Claude Fable 5 has 61 scored results on Noometry and GPT-6 Luna has 18.