Model comparison
Claude 3.5 Sonnet vs GPT-5.6 Terra
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 34.6 on the Noometry Index.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. Claude 3.5 Sonnet scores higher in 0 categories and GPT-5.6 Terra in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 19.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 8.5% for Claude 3.5 Sonnet and 99.7% for GPT-5.6 Terra.
Side by side
| Claude 3.5 Sonnet | GPT-5.6 Terra | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 34.6 | 59.2 |
| Released | 2024-06-20 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $12 |
| Results tracked | 60 | 52 |
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Category by category
Coding GPT-5.6 Terra leads
Claude 3.5 Sonnet: 39.0 (#165), GPT-5.6 Terra: 57.7 (#19)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| WeirdML | 40% | 78.3% |
| LMArena Coding | 1342 | 1484 |
| DeepSWE | — | 69.6% |
| FrontierCode | — | 41.3% |
| Aider Polyglot | 51.6% | — |
| CursorBench | — | 41.3% |
| LMArena WebDev | — | 1522 |
| SciCode | — | 55% |
| GSO | 4.6% | — |
| BigCodeBench Instruct | 46.8% | — |
| LiveBench Coding | 67.1% | — |
| BigCodeBench Complete | 58.6% | — |
| CadEval | 48% | — |
| ALE-Bench | — | 1,951 |
| HumanEval+ | 81.7% | — |
| MBPP+ | 74.3% | — |
Agentic & Tool Use GPT-5.6 Terra leads
Claude 3.5 Sonnet: 32.3 (#67), GPT-5.6 Terra: 40.1 (#25)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| BALROG | 32.6% | 53.2% |
| APEX-Agents | — | 58.2% |
| TheAgentCompany | 24% | — |
| Cybench | 17.5% | — |
| GDP.pdf | — | 24.7% |
| METR Time Horizons | 45.2% | — |
| Vending-Bench 2 | — | 7,343 |
Reasoning GPT-5.6 Terra leads
Claude 3.5 Sonnet: 23.1 (#183), GPT-5.6 Terra: 60.7 (#21)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| SimpleBench | 41.4% | 48.9% |
| LMArena Hard Prompts | 1305 | 1468 |
| DTBench | 67.8% | 93.3% |
| Epoch Capabilities Index | 133.55 | 159.62 |
| ARC-AGI-2 | — | 83.9% |
| Kagi LLM Benchmark | — | 51.3% |
| NYT Connections (extended) | — | 78.4% |
| ARC-AGI-1 | — | 96.5% |
| CritPt | — | 30% |
| Chess Puzzles | — | 54% |
| EnigmaEval | 0.9% | — |
| LiveBench Reasoning | 56.7% | — |
| Mystery Game Puzzles | — | 35% |
| LiveBench Data Analysis | 55% | — |
| LMCA | — | 55% |
| Surface Evolver Bench | — | 83.8% |
| ForecastBench | 60.7 | — |
| LiveBench | 59% | — |
Math GPT-5.6 Terra leads
Claude 3.5 Sonnet: 19.2 (#288), GPT-5.6 Terra: 81.6 (#12)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 8.5% | 99.7% |
| LMArena Math | 1307 | 1466 |
| FrontierMath (Tiers 1-3) | — | 86% |
| FrontierMath Tier 4 | — | 70.7% |
| ProofBench | — | 74% |
| Omni-MATH | 27.6% | — |
| LiveBench Math | 52.3% | — |
| MATH Level 5 | 56.9% | — |
| FrontierMath (Feb 2025 set) | 2.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge GPT-5.6 Terra leads
Claude 3.5 Sonnet: 28.6 (#245), GPT-5.6 Terra: 61.2 (#30)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | 55.3% | 93.3% |
| LMArena Expert | 1265 | 1492 |
| Humanity's Last Exam | 4.1% | — |
| SimpleQA Verified | — | 43.2% |
| MMLU-Pro | 77.7% | — |
| Confabulations | 19.9% | — |
| GPQA (HELM) | 56.5% | — |
| MMLU | 87.3% | — |
Multimodal GPT-5.6 Terra leads
Claude 3.5 Sonnet: 26.5 (#120), GPT-5.6 Terra: 47.3 (#11)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | 1125 | 1271 |
| Video-MME | 60% | — |
| GeoBench | 62% | — |
| VPCT | 33% | — |
| Blueprint-Bench 2 | — | 30.8% |
| Furniture Assembly | — | 54.2% |
| LMArena Document | — | 1472 |
Multilingual GPT-5.6 Terra leads
Claude 3.5 Sonnet: 43.2 (#185), GPT-5.6 Terra: 54.4 (#44)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | 1283 | 1439 |
| LMArena Chinese | 1272 | 1513 |
| LMArena French | 1305 | 1471 |
| LMArena German | 1297 | 1460 |
| LMArena Japanese | 1234 | 1457 |
| LMArena Korean | 1200 | 1425 |
| LMArena Russian | 1306 | 1450 |
| LMArena Spanish | 1290 | 1448 |
Instruction Following GPT-5.6 Terra leads
Claude 3.5 Sonnet: 68.8 (#182), GPT-5.6 Terra: 76.4 (#40)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | 1297 | 1454 |
| LiveBench Instruction Following | 69.3% | — |
| IFEval | 85.5% | — |
Long Context GPT-5.6 Terra leads
Claude 3.5 Sonnet: 39.9 (#167), GPT-5.6 Terra: 44.4 (#68)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | 1311 | 1451 |
Writing & Preference GPT-5.6 Terra leads
Claude 3.5 Sonnet: 52.9 (#164), GPT-5.6 Terra: 70.2 (#23)
| Benchmark | Claude 3.5 Sonnet | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | 1298 | 1447 |
| LMArena Creative Writing | 1292 | 1410 |
| EQ-Bench Creative Writing | 1451 | 1855 |
| LMArena Multi-Turn | 1326 | 1449 |
| Short-Story Creative Writing | 80.3% | — |
| WildBench | 79.2% | — |
| EQ-Bench 4 | — | 1234 |
| LiveBench Language | 53.8% | — |
Frequently asked questions
Is Claude 3.5 Sonnet better than GPT-5.6 Terra?
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 34.6 on the Noometry Index.
Is Claude 3.5 Sonnet or GPT-5.6 Terra better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 39.0 in the Noometry coding category.
How many benchmarks do Claude 3.5 Sonnet and GPT-5.6 Terra share?
26 benchmarks have published results for both models. Claude 3.5 Sonnet has 60 scored results on Noometry and GPT-5.6 Terra has 52.