Model comparison
Claude Fable 5.1 vs GPT-5.2
Claude Fable 5.1 is the stronger model overall, scoring 69.0 to 54.1 on the Noometry Index. GPT-5.2 costs 4.2× less per token, which makes it the better buy when Claude Fable 5.1's lead doesn't matter for your workload.
Last verified . 42 shared benchmarks.
Summary
- They share 42 benchmarks with published results for both. Claude Fable 5.1 scores higher in 10 categories and GPT-5.2 in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Fable 5.1 leads 89.6 to 60.0.
- The biggest single-benchmark swing is ProofBench: 100% for Claude Fable 5.1 and 15% for GPT-5.2.
- GPT-5.2 is cheaper at $1.75 / $14 per million input/output tokens, against $10 / $50 for Claude Fable 5.1.
- Claude Fable 5.1 accepts more context: 1M tokens versus 400K.
Side by side
| Claude Fable 5.1 | GPT-5.2 | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 69.0 | 54.1 |
| Released | 2026-09-01 | 2025-12-11 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $10 | $1.75 |
| Output $ / M tokens | $50 | $14 |
| Results tracked | 52 | 67 |
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Category by category
Coding Claude Fable 5.1 leads
Claude Fable 5.1: 74.7 (#1), GPT-5.2: 51.6 (#37)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| LMArena WebDev | 1744 | 1416 |
| GSO | 88.2% | 27.4% |
| WeirdML | 92.9% | 72.2% |
| LMArena Coding | 1528 | 1447 |
| ALE-Bench | 2,143 | 1,294 |
| SWE-bench Verified | — | 73.8% |
| FrontierCode | 50.9% | — |
| SWE-bench Verified (bash only) | — | 72.8% |
| CursorBench | 51.8% | — |
| SWE-bench Multilingual | — | 66.7% |
| FrontierSWE | 56.3% | — |
| SciCode | 63.1% | — |
| MirrorCode | 73.3% | — |
| AlgoTune | — | 2.05 |
Agentic & Tool Use Claude Fable 5.1 leads
Claude Fable 5.1: 50.7 (#5), GPT-5.2: 40.2 (#24)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| Remote Labor Index | 17.9% | 2.5% |
| Vending-Bench 2 | 5,422 | 3,591 |
| Terminal-Bench | — | 64.9% |
| APEX-Agents | 68.6% | — |
| Berkeley Function Calling Leaderboard | — | 55.9% |
| GDPval | — | 49.7% |
| τ²-bench Airline | — | 83% |
| τ²-bench Banking | — | 32.2% |
| τ²-bench Retail | — | 81.6% |
| τ²-bench Telecom | — | 89.7% |
| DeepResearch Bench | — | 41.1% |
| GDP.pdf | 29.6% | — |
| LMArena Search | — | 1207 |
| METR Time Horizons | — | 75.3% |
Reasoning Claude Fable 5.1 leads
Claude Fable 5.1: 76.7 (#7), GPT-5.2: 50.2 (#35)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| ARC-AGI-2 | 90% | 52.9% |
| NYT Connections (extended) | 90% | 83.6% |
| ARC-AGI-1 | 97.5% | 86.2% |
| Chess Puzzles | 47% | 49% |
| EBR-Bench | 57.1% | 23% |
| LMArena Hard Prompts | 1526 | 1445 |
| Mystery Game Puzzles | 58% | 23% |
| DTBench | 97.6% | 90.9% |
| LMCA | 65.5% | 43.9% |
| Epoch Capabilities Index | 164.7 | 153.45 |
| SimpleBench | — | 45.8% |
| Kagi LLM Benchmark | — | 73.3% |
| CritPt | 31.1% | — |
| EnigmaEval | — | 10.4% |
| ForecastBench | — | 60.1 |
Math Claude Fable 5.1 leads
Claude Fable 5.1: 89.6 (#4), GPT-5.2: 60.0 (#38)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 90.2% | 67.4% |
| FrontierMath Tier 4 | 87.8% | 31.7% |
| OTIS Mock AIME 2024-2025 | 100% | 96.1% |
| ProofBench | 100% | 15% |
| LMArena Math | 1525 | 1440 |
| MathArena Final-Answer Competitions | — | 72% |
| FrontierMath (Feb 2025 set) | — | 40.7% |
| FrontierMath Erdős | 0% | — |
| FrontierMath Tier 4 (v1) | — | 18.8% |
Knowledge Claude Fable 5.1 leads
Claude Fable 5.1: 69.6 (#6), GPT-5.2: 59.3 (#32)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| Humanity's Last Exam | 46.5% | 27.8% |
| SimpleQA Verified | 70.8% | 37.1% |
| LMArena Expert | 1535 | 1445 |
| GPQA Diamond | — | 91.4% |
| Vectara Hallucination Rate | — | 8.4% |
Multimodal Claude Fable 5.1 leads
Claude Fable 5.1: 53.9 (#4), GPT-5.2: 51.3 (#7)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| LMArena Vision | 1318 | 1268 |
| Furniture Assembly | 70% | 38.3% |
| LMArena Document | 1513 | 1405 |
| VPCT | — | 84% |
| Blueprint-Bench 2 | 41.9% | — |
Multilingual Claude Fable 5.1 leads
Claude Fable 5.1: 59.1 (#3), GPT-5.2: 53.4 (#67)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| LMArena Non-English | 1507 | 1425 |
| LMArena Chinese | 1586 | 1460 |
| LMArena French | 1525 | 1455 |
| LMArena German | 1500 | 1448 |
| LMArena Japanese | 1543 | 1420 |
| LMArena Korean | 1534 | 1392 |
| LMArena Russian | 1521 | 1440 |
| LMArena Spanish | 1516 | 1433 |
Instruction Following Claude Fable 5.1 leads
Claude Fable 5.1: 79.2 (#6), GPT-5.2: 74.7 (#89)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| LMArena Instruction Following | 1517 | 1417 |
Long Context Claude Fable 5.1 leads
Claude Fable 5.1: 46.7 (#20), GPT-5.2: 44.0 (#78)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| LMArena Longer Query | 1522 | 1428 |
| CL-bench | — | 18.2% |
Writing & Preference Claude Fable 5.1 leads
Claude Fable 5.1: 79.2 (#2), GPT-5.2: 66.8 (#32)
| Benchmark | Claude Fable 5.1 | GPT-5.2 |
|---|---|---|
| LMArena Text | 1510 | 1439 |
| LMArena Creative Writing | 1507 | 1401 |
| EQ-Bench Creative Writing | 2162 | 1703 |
| LMArena Multi-Turn | 1492 | 1458 |
Frequently asked questions
Is Claude Fable 5.1 better than GPT-5.2?
Claude Fable 5.1 is the stronger model overall, scoring 69.0 to 54.1 on the Noometry Index. GPT-5.2 costs 4.2× less per token, which makes it the better buy when Claude Fable 5.1's lead doesn't matter for your workload.
Which is cheaper, Claude Fable 5.1 or GPT-5.2?
GPT-5.2 is cheaper. It lists at $1.75 per million input tokens and $14 per million output tokens; Claude Fable 5.1 lists at $10 and $50.
Is Claude Fable 5.1 or GPT-5.2 better for coding?
Claude Fable 5.1 scores higher on coding benchmarks: 74.7 versus 51.6 in the Noometry coding category.
Which has the bigger context window?
Claude Fable 5.1 does, with 1M tokens against 400K.
How many benchmarks do Claude Fable 5.1 and GPT-5.2 share?
42 benchmarks have published results for both models. Claude Fable 5.1 has 52 scored results on Noometry and GPT-5.2 has 67.