Model comparison
Claude 3.7 Sonnet vs GPT-5.2
GPT-5.2 is the stronger model overall, scoring 54.1 to 39.5 on the Noometry Index.
Last verified . 35 shared benchmarks.
Summary
- They share 35 benchmarks with published results for both. Claude 3.7 Sonnet scores higher in 1 category and GPT-5.2 in 9 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.2 leads 50.2 to 18.6.
- The biggest single-benchmark swing is ARC-AGI-1: 28.6% for Claude 3.7 Sonnet and 86.2% for GPT-5.2.
Side by side
| Claude 3.7 Sonnet | GPT-5.2 | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 39.5 | 54.1 |
| Released | 2025-02-24 | 2025-12-11 |
| Weights | Proprietary | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $1.75 |
| Output $ / M tokens | — | $14 |
| Results tracked | 58 | 67 |
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Category by category
Coding GPT-5.2 leads
Claude 3.7 Sonnet: 40.6 (#136), GPT-5.2: 51.6 (#37)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| SWE-bench Verified | 61% | 73.8% |
| SWE-bench Verified (bash only) | 52.8% | 72.8% |
| GSO | 3.8% | 27.4% |
| LMArena Coding | 1361 | 1447 |
| Aider Polyglot | 64.9% | — |
| LMArena WebDev | — | 1416 |
| SWE-bench Multilingual | — | 66.7% |
| WeirdML | — | 72.2% |
| LiveBench Coding | 74.5% | — |
| CadEval | 54% | — |
| ALE-Bench | — | 1,294 |
| AlgoTune | — | 2.05 |
Agentic & Tool Use GPT-5.2 leads
Claude 3.7 Sonnet: 34.1 (#50), GPT-5.2: 40.2 (#24)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| DeepResearch Bench | 43.6% | 41.1% |
| METR Time Horizons | 60% | 75.3% |
| Terminal-Bench | — | 64.9% |
| Berkeley Function Calling Leaderboard | — | 55.9% |
| GDPval | — | 49.7% |
| Remote Labor Index | — | 2.5% |
| TheAgentCompany | 30.9% | — |
| τ²-bench Airline | — | 83% |
| τ²-bench Banking | — | 32.2% |
| τ²-bench Retail | — | 81.6% |
| τ²-bench Telecom | — | 89.7% |
| Cybench | 20% | — |
| OSWorld | 35.8% | — |
| LMArena Search | — | 1207 |
| Vending-Bench 2 | — | 3,591 |
Reasoning GPT-5.2 leads
Claude 3.7 Sonnet: 18.6 (#277), GPT-5.2: 50.2 (#35)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| ARC-AGI-2 | 0.9% | 52.9% |
| SimpleBench | 46.4% | 45.8% |
| ARC-AGI-1 | 28.6% | 86.2% |
| EnigmaEval | 4.2% | 10.4% |
| LMArena Hard Prompts | 1333 | 1445 |
| Epoch Capabilities Index | 141.16 | 153.45 |
| ForecastBench | 61.8 | 60.1 |
| Kagi LLM Benchmark | — | 73.3% |
| NYT Connections (extended) | — | 83.6% |
| Chess Puzzles | — | 49% |
| EBR-Bench | — | 23% |
| LiveBench Reasoning | 87.8% | — |
| Mystery Game Puzzles | — | 23% |
| DTBench | — | 90.9% |
| LiveBench Data Analysis | 74% | — |
| LMCA | — | 43.9% |
| LiveBench | 76.1% | — |
Math GPT-5.2 leads
Claude 3.7 Sonnet: 37.5 (#153), GPT-5.2: 60.0 (#38)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 57.8% | 96.1% |
| LMArena Math | 1337 | 1440 |
| FrontierMath (Feb 2025 set) | 4.1% | 40.7% |
| FrontierMath (Tiers 1-3) | — | 67.4% |
| FrontierMath Tier 4 | — | 31.7% |
| MathArena Final-Answer Competitions | — | 72% |
| ProofBench | — | 15% |
| Omni-MATH | 33% | — |
| LiveBench Math | 79% | — |
| MATH Level 5 | 91.2% | — |
| FrontierMath Tier 4 (v1) | — | 18.8% |
Knowledge GPT-5.2 leads
Claude 3.7 Sonnet: 39.8 (#130), GPT-5.2: 59.3 (#32)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| GPQA Diamond | 79.7% | 91.4% |
| Humanity's Last Exam | 8% | 27.8% |
| LMArena Expert | 1321 | 1445 |
| SimpleQA Verified | — | 37.1% |
| MMLU-Pro | 78.4% | — |
| Confabulations | 14.7% | — |
| Vectara Hallucination Rate | — | 8.4% |
| GPQA (HELM) | 60.8% | — |
Multimodal GPT-5.2 leads
Claude 3.7 Sonnet: 33.7 (#95), GPT-5.2: 51.3 (#7)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| LMArena Vision | 1169 | 1268 |
| VPCT | 39% | 84% |
| GeoBench | 68% | — |
| Furniture Assembly | — | 38.3% |
| LMArena Document | — | 1405 |
| SpatialViz-Bench | 33.9% | — |
Multilingual GPT-5.2 leads
Claude 3.7 Sonnet: 44.1 (#179), GPT-5.2: 53.4 (#67)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| LMArena Non-English | 1296 | 1425 |
| LMArena Chinese | 1299 | 1460 |
| LMArena French | 1303 | 1455 |
| LMArena German | 1301 | 1448 |
| LMArena Japanese | 1267 | 1420 |
| LMArena Korean | 1249 | 1392 |
| LMArena Russian | 1311 | 1440 |
| LMArena Spanish | 1298 | 1433 |
Instruction Following GPT-5.2 leads
Claude 3.7 Sonnet: 72.9 (#125), GPT-5.2: 74.7 (#89)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| LMArena Instruction Following | 1352 | 1417 |
| LiveBench Instruction Following | 81.3% | — |
| IFEval | 83.4% | — |
Long Context Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 50.3 (#10), GPT-5.2: 44.0 (#78)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| LMArena Longer Query | 1373 | 1428 |
| Fiction.LiveBench | 83.3% | — |
| CL-bench | — | 18.2% |
Writing & Preference GPT-5.2 leads
Claude 3.7 Sonnet: 54.4 (#150), GPT-5.2: 66.8 (#32)
| Benchmark | Claude 3.7 Sonnet | GPT-5.2 |
|---|---|---|
| LMArena Text | 1314 | 1439 |
| LMArena Creative Writing | 1332 | 1401 |
| EQ-Bench Creative Writing | 1412 | 1703 |
| LMArena Multi-Turn | 1339 | 1458 |
| Short-Story Creative Writing | 81.1% | — |
| WildBench | 81.4% | — |
| LiveBench Language | 59.9% | — |
Frequently asked questions
Is Claude 3.7 Sonnet better than GPT-5.2?
GPT-5.2 is the stronger model overall, scoring 54.1 to 39.5 on the Noometry Index.
Is Claude 3.7 Sonnet or GPT-5.2 better for coding?
GPT-5.2 scores higher on coding benchmarks: 51.6 versus 40.6 in the Noometry coding category.
How many benchmarks do Claude 3.7 Sonnet and GPT-5.2 share?
35 benchmarks have published results for both models. Claude 3.7 Sonnet has 58 scored results on Noometry and GPT-5.2 has 67.