Model comparison
Claude Sonnet 4.6 vs GPT-5 Pro
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 46.4 on the Noometry Index.
Last verified . 5 shared benchmarks.
Summary
- They share 5 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 3 categories and GPT-5 Pro in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Sonnet 4.6 leads 46.1 to 38.9.
- The biggest single-benchmark swing is ARC-AGI-2: 60.4% for Claude Sonnet 4.6 and 18.3% for GPT-5 Pro.
- Claude Sonnet 4.6 is cheaper at $3 / $15 per million input/output tokens, against $15 / $120 for GPT-5 Pro.
- Claude Sonnet 4.6 accepts more context: 1M tokens versus 400K.
Side by side
| Claude Sonnet 4.6 | GPT-5 Pro | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 50.3 | 46.4 |
| Released | 2026-02-17 | 2025-10-06 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 400K |
| Max output | 128K | 272K |
| Input $ / M tokens | $3 | $15 |
| Output $ / M tokens | $15 | $120 |
| Results tracked | 57 | 12 |
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Category by category
Coding Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.3 (#67), GPT-5 Pro: 44.0 (#80)
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| WeirdML | 66.1% | 60.4% |
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| LMArena WebDev | 1522 | — |
| SciCode | 46.8% | — |
| LMArena Coding | 1504 | — |
| ALE-Bench | 1,327 | — |
| AlgoTune | — | 1.31 |
Agentic & Tool Use Not comparable
Claude Sonnet 4.6: 39.1 (#28), GPT-5 Pro: —
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#45), GPT-5 Pro: 38.9 (#62)
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| ARC-AGI-2 | 60.4% | 18.3% |
| ARC-AGI-1 | 86.5% | 70.2% |
| Epoch Capabilities Index | 152.24 | 150.28 |
| SimpleBench | — | 61.6% |
| Kagi LLM Benchmark | — | 76.8% |
| NYT Connections (extended) | 80.9% | — |
| CritPt | 3.1% | — |
| Chess Puzzles | 13% | — |
| EnigmaEval | — | 18.8% |
| Thematic Generalization | 76.3% | — |
| LMArena Hard Prompts | 1484 | — |
| Mystery Game Puzzles | 16% | — |
| DTBench | 89.9% | — |
| LMCA | 46.5% | — |
| ForecastBench | 62 | — |
Math Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 52.9 (#49), GPT-5 Pro: 48.5 (#63)
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| FrontierMath Tier 4 (v1) | 8.3% | 14.6% |
| FrontierMath (Tiers 1-3) | — | 55.8% |
| FrontierMath Tier 4 | — | 19.5% |
| OTIS Mock AIME 2024-2025 | 85.8% | — |
| ProofBench | 45% | — |
| LMArena Math | 1462 | — |
| FrontierMath (Feb 2025 set) | 32.4% | — |
Knowledge GPT-5 Pro leads
Claude Sonnet 4.6: 51.7 (#65), GPT-5 Pro: 56.7 (#42)
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| GPQA Diamond | 87.4% | — |
| Humanity's Last Exam | — | 31.6% |
| SimpleQA Verified | 35.5% | — |
| Vectara Hallucination Rate | 10.6% | — |
| LMArena Expert | 1500 | — |
Multimodal Not comparable
Claude Sonnet 4.6: 38.0 (#68), GPT-5 Pro: —
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual Not comparable
Claude Sonnet 4.6: 54.4 (#41), GPT-5 Pro: —
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| LMArena Non-English | 1440 | — |
| LMArena Chinese | 1491 | — |
| LMArena French | 1465 | — |
| LMArena German | 1428 | — |
| LMArena Japanese | 1420 | — |
| LMArena Korean | 1411 | — |
| LMArena Russian | 1440 | — |
| LMArena Spanish | 1464 | — |
Instruction Following Not comparable
Claude Sonnet 4.6: 77.4 (#25), GPT-5 Pro: —
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| LMArena Instruction Following | 1475 | — |
Long Context Not comparable
Claude Sonnet 4.6: 45.3 (#44), GPT-5 Pro: —
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| LMArena Longer Query | 1479 | — |
Writing & Preference Not comparable
Claude Sonnet 4.6: 70.2 (#22), GPT-5 Pro: —
| Benchmark | Claude Sonnet 4.6 | GPT-5 Pro |
|---|---|---|
| LMArena Text | 1458 | — |
| LMArena Creative Writing | 1435 | — |
| EQ-Bench Creative Writing | 1810 | — |
| EQ-Bench 4 | 1207 | — |
| LMArena Multi-Turn | 1464 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than GPT-5 Pro?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 46.4 on the Noometry Index.
Which is cheaper, Claude Sonnet 4.6 or GPT-5 Pro?
Claude Sonnet 4.6 is cheaper. It lists at $3 per million input tokens and $15 per million output tokens; GPT-5 Pro lists at $15 and $120.
Is Claude Sonnet 4.6 or GPT-5 Pro better for coding?
Claude Sonnet 4.6 scores higher on coding benchmarks: 46.3 versus 44.0 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 4.6 does, with 1M tokens against 400K.
How many benchmarks do Claude Sonnet 4.6 and GPT-5 Pro share?
5 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and GPT-5 Pro has 12.