Model comparison
Claude Opus 4.7 vs GPT-5.2 Pro
Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 52.2 on the Noometry Index.
Last verified . 8 shared benchmarks.
Summary
- They share 8 benchmarks with published results for both. Claude Opus 4.7 scores higher in 2 categories and GPT-5.2 Pro in 0 categories; 2 gaps are clear of the uncertainty.
- The biggest single-benchmark swing is NYT Connections (extended): 39% for Claude Opus 4.7 and 79.3% for GPT-5.2 Pro.
- Claude Opus 4.7 is cheaper at $5 / $25 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- Claude Opus 4.7 accepts more context: 1M tokens versus 400K.
Side by side
| Claude Opus 4.7 | GPT-5.2 Pro | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.4 | 52.2 |
| Released | 2026-04-14 | 2025-12-11 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $5 | $21 |
| Output $ / M tokens | $25 | $168 |
| Results tracked | 66 | 8 |
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Category by category
Coding Not comparable
Claude Opus 4.7: 59.9 (#10), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| LMArena WebDev | 1557 | — |
| SciCode | 54.5% | — |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| LMArena Coding | 1519 | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.7: 47.9 (#8), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |
Reasoning Claude Opus 4.7 leads
Claude Opus 4.7: 53.7 (#24), GPT-5.2 Pro: 51.8 (#31)
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| ARC-AGI-2 | 75.8% | 54.2% |
| SimpleBench | 61.7% | 57.4% |
| NYT Connections (extended) | 39% | 79.3% |
| ARC-AGI-1 | 93.5% | 90.5% |
| Epoch Capabilities Index | 156.39 | 155.41 |
| Kagi LLM Benchmark | 80.7% | — |
| CritPt | 12% | — |
| Chess Puzzles | 30% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| LMArena Hard Prompts | 1507 | — |
| Mystery Game Puzzles | 28% | — |
| DTBench | 94.7% | — |
| LMCA | 52.2% | — |
| ForecastBench | 60.3 | — |
Math Claude Opus 4.7 leads
Claude Opus 4.7: 66.5 (#20), GPT-5.2 Pro: 64.8 (#23)
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 70.2% | 74% |
| FrontierMath Tier 4 | 31.7% | 46% |
| FrontierMath Tier 4 (v1) | 22.9% | 31.3% |
| MathArena Final-Answer Competitions | 73.6% | — |
| OTIS Mock AIME 2024-2025 | 97.8% | — |
| ProofBench | 54% | — |
| LMArena Math | 1499 | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
Knowledge Not comparable
Claude Opus 4.7: 62.6 (#20), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| GPQA Diamond | 90.2% | — |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
| Vectara Hallucination Rate | 12% | — |
| LMArena Expert | 1521 | — |
Multimodal Not comparable
Claude Opus 4.7: 41.5 (#29), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| LMArena Vision | 1317 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |
Multilingual Not comparable
Claude Opus 4.7: 57.5 (#9), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| LMArena Non-English | 1481 | — |
| LMArena Chinese | 1530 | — |
| LMArena French | 1505 | — |
| LMArena German | 1494 | — |
| LMArena Japanese | 1472 | — |
| LMArena Korean | 1466 | — |
| LMArena Russian | 1494 | — |
| LMArena Spanish | 1497 | — |
Instruction Following Not comparable
Claude Opus 4.7: 78.6 (#9), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| LMArena Instruction Following | 1498 | — |
Long Context Not comparable
Claude Opus 4.7: 46.1 (#24), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| LMArena Longer Query | 1505 | — |
Writing & Preference Not comparable
Claude Opus 4.7: 75.3 (#8), GPT-5.2 Pro: —
| Benchmark | Claude Opus 4.7 | GPT-5.2 Pro |
|---|---|---|
| LMArena Text | 1491 | — |
| LMArena Creative Writing | 1486 | — |
| EQ-Bench Creative Writing | 1914 | — |
| EQ-Bench 4 | 1311 | — |
| LMArena Multi-Turn | 1506 | — |
Frequently asked questions
Is Claude Opus 4.7 better than GPT-5.2 Pro?
Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 52.2 on the Noometry Index.
Which is cheaper, Claude Opus 4.7 or GPT-5.2 Pro?
Claude Opus 4.7 is cheaper. It lists at $5 per million input tokens and $25 per million output tokens; GPT-5.2 Pro lists at $21 and $168.
Which has the bigger context window?
Claude Opus 4.7 does, with 1M tokens against 400K.
How many benchmarks do Claude Opus 4.7 and GPT-5.2 Pro share?
8 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and GPT-5.2 Pro has 8.