Model comparison
Claude Opus 4.6 vs GPT-5.6 Terra
Claude Opus 4.6 and GPT-5.6 Terra score almost the same on the Noometry Index (58.2 vs 59.2), so choose on price, context window or the category you care about most.
Last verified . 44 shared benchmarks.
Summary
- They share 44 benchmarks with published results for both. Claude Opus 4.6 scores higher in 6 categories and GPT-5.6 Terra in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 63.0.
- The biggest single-benchmark swing is FrontierMath Tier 4: 26.8% for Claude Opus 4.6 and 70.7% for GPT-5.6 Terra.
- GPT-5.6 Terra is cheaper at $2 / $12 per million input/output tokens, against $5 / $25 for Claude Opus 4.6.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Opus 4.6 | GPT-5.6 Terra | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 58.2 | 59.2 |
| Released | 2026-02-04 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $5 | $2 |
| Output $ / M tokens | $25 | $12 |
| Results tracked | 68 | 52 |
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Category by category
Coding Too close to call
Claude Opus 4.6: 57.2 (#20), GPT-5.6 Terra: 57.7 (#19)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| FrontierCode | 26.6% | 41.3% |
| LMArena WebDev | 1547 | 1522 |
| WeirdML | 78% | 78.3% |
| LMArena Coding | 1536 | 1484 |
| ALE-Bench | 996.5 | 1,951 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | — | 69.6% |
| SWE-bench Verified (bash only) | 75.6% | — |
| CursorBench | — | 41.3% |
| SWE-bench Multilingual | 72% | — |
| SciCode | — | 55% |
| GSO | 41.2% | — |
| AlgoTune | 1.47 | — |
Agentic & Tool Use Claude Opus 4.6 leads
Claude Opus 4.6: 51.1 (#4), GPT-5.6 Terra: 40.1 (#25)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| APEX-Agents | 46.3% | 58.2% |
| Vending-Bench 2 | 8,018 | 7,343 |
| Terminal-Bench | 79.8% | — |
| Remote Labor Index | 4.2% | — |
| τ²-bench Banking | 27.3% | — |
| Cybench | 93% | — |
| DeepResearch Bench | 55.3% | — |
| BALROG | — | 53.2% |
| GBAEval | 44.1% | — |
| GDP.pdf | — | 24.7% |
| LMArena Search | 1253 | — |
| METR Time Horizons | 78.9% | — |
Reasoning GPT-5.6 Terra leads
Claude Opus 4.6: 57.8 (#23), GPT-5.6 Terra: 60.7 (#21)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| ARC-AGI-2 | 69.2% | 83.9% |
| SimpleBench | 67.6% | 48.9% |
| Kagi LLM Benchmark | 83.6% | 51.3% |
| NYT Connections (extended) | 92.1% | 78.4% |
| ARC-AGI-1 | 94% | 96.5% |
| Chess Puzzles | 17% | 54% |
| LMArena Hard Prompts | 1527 | 1468 |
| Mystery Game Puzzles | 25% | 35% |
| DTBench | 91.2% | 93.3% |
| LMCA | 55.8% | 55% |
| Epoch Capabilities Index | 155.24 | 159.62 |
| CritPt | — | 30% |
| EnigmaEval | 7.6% | — |
| Thematic Generalization | 80.6% | — |
| EBR-Bench | 12.7% | — |
| Surface Evolver Bench | — | 83.8% |
| ForecastBench | 60 | — |
Math GPT-5.6 Terra leads
Claude Opus 4.6: 63.0 (#31), GPT-5.6 Terra: 81.6 (#12)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | 86% |
| FrontierMath Tier 4 | 26.8% | 70.7% |
| OTIS Mock AIME 2024-2025 | 94.4% | 99.7% |
| ProofBench | 50% | 74% |
| LMArena Math | 1519 | 1466 |
| MathArena Final-Answer Competitions | 78.5% | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
Knowledge Too close to call
Claude Opus 4.6: 61.9 (#26), GPT-5.6 Terra: 61.2 (#30)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | 90.5% | 93.3% |
| SimpleQA Verified | 47% | 43.2% |
| LMArena Expert | 1546 | 1492 |
| Humanity's Last Exam | 34.4% | — |
| Vectara Hallucination Rate | 12.2% | — |
Multimodal GPT-5.6 Terra leads
Claude Opus 4.6: 37.3 (#74), GPT-5.6 Terra: 47.3 (#11)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | 1316 | 1271 |
| Furniture Assembly | 28.3% | 54.2% |
| LMArena Document | 1507 | 1472 |
| Blueprint-Bench 2 | — | 30.8% |
Multilingual Claude Opus 4.6 leads
Claude Opus 4.6: 57.9 (#6), GPT-5.6 Terra: 54.4 (#44)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | 1489 | 1439 |
| LMArena Chinese | 1551 | 1513 |
| LMArena French | 1513 | 1471 |
| LMArena German | 1502 | 1460 |
| LMArena Japanese | 1484 | 1457 |
| LMArena Korean | 1464 | 1425 |
| LMArena Russian | 1497 | 1450 |
| LMArena Spanish | 1510 | 1448 |
Instruction Following Claude Opus 4.6 leads
Claude Opus 4.6: 79.5 (#4), GPT-5.6 Terra: 76.4 (#40)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | 1523 | 1454 |
Long Context Claude Opus 4.6 leads
Claude Opus 4.6: 48.1 (#13), GPT-5.6 Terra: 44.4 (#68)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | 1520 | 1451 |
| CL-bench | 20.7% | — |
| CL-bench Life | 17% | — |
Writing & Preference Claude Opus 4.6 leads
Claude Opus 4.6: 73.5 (#10), GPT-5.6 Terra: 70.2 (#23)
| Benchmark | Claude Opus 4.6 | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | 1503 | 1447 |
| LMArena Creative Writing | 1505 | 1410 |
| EQ-Bench Creative Writing | 1809 | 1855 |
| EQ-Bench 4 | 1223 | 1234 |
| LMArena Multi-Turn | 1513 | 1449 |
Frequently asked questions
Is Claude Opus 4.6 better than GPT-5.6 Terra?
Claude Opus 4.6 and GPT-5.6 Terra score almost the same on the Noometry Index (58.2 vs 59.2), so choose on price, context window or the category you care about most.
Which is cheaper, Claude Opus 4.6 or GPT-5.6 Terra?
GPT-5.6 Terra is cheaper. It lists at $2 per million input tokens and $12 per million output tokens; Claude Opus 4.6 lists at $5 and $25.
Is Claude Opus 4.6 or GPT-5.6 Terra better for coding?
They score almost the same on coding (57.2 vs 57.7); test both on your own repository before choosing.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 1M.
How many benchmarks do Claude Opus 4.6 and GPT-5.6 Terra share?
44 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and GPT-5.6 Terra has 52.