Model comparison
Claude Opus 4.7 vs GPT-5.6 Terra
Head-to-head evidence from 15 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 #12 (Supported); GPT-5.6 Terra #11 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 and GPT-5.6 Terra share 15 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to Claude Opus 4.7; 29 to GPT-5.6 Terra.
Updated July 23, 2026- Shared results
- 15
- Claude Opus 4.7 only
- 6
- GPT-5.6 Terra only
- 29
- Comparable categories
- 1 / 8
Pick GPT-5.6 Terra if you want the stronger benchmark profile. Claude Opus 4.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 7 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.6 Terra has the cleaner BenchAlign overall profile here, landing at 72.57 versus 71.94. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.6 Terra's sharpest advantage is in mathematics, where it averages 80.8 against 38.6. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 22.917% to 68.300%.
Claude Opus 4.7 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $2.50 input / $15.00 output per 1M tokens for GPT-5.6 Terra. GPT-5.6 Terra is the reasoning model in the pair, while Claude Opus 4.7 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude Opus 4.7 | Δ | GPT-5.6 Terra |
|---|---|---|---|
| Math | Claude Opus 4.738.6 | Margin→ 42.2 | GPT-5.6 Terra80.8 |
| Agentic | Claude Opus 4.7Not measured | MarginNo overlap | GPT-5.6 Terra87.4 |
| Coding | Claude Opus 4.7Not measured | MarginNo overlap | GPT-5.6 Terra63.4 |
| Knowledge | Claude Opus 4.7Not measured | MarginNo overlap | GPT-5.6 Terra92.9 |
| Multimodal | Claude Opus 4.7Not measured | MarginNo overlap | GPT-5.6 Terra80.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 22.917%B 68.300%Winner: GPT-5.6 TerraΔ 45.4FrontierMath v2 (Tier 4): Claude Opus 4.7 scored 22.917%; GPT-5.6 Terra scored 68.300%. GPT-5.6 Terra wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 43.793%B 84.900%Winner: GPT-5.6 TerraΔ 41.1FrontierMath v2 (Tiers 1-3): Claude Opus 4.7 scored 43.793%; GPT-5.6 Terra scored 84.900%. GPT-5.6 Terra wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 | GPT-5.6 Terra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7$5 input / $25 output | GPT-5.6 Terra$2.5 input / $15 output | GPT-5.6 Terra has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7Not available | GPT-5.6 TerraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7Not available | GPT-5.6 TerraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.71M | GPT-5.6 Terra1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic19 benchmarks
| Benchmark | Claude Opus 4.7 | GPT-5.6 Terra | Result |
|---|---|---|---|
| τ²-bench resultsSource | 74% | 86.3% | GPT-5.6 Terra leads |
| Gert LabsSource | 65.59% | — | Not comparable |
| ResearchClawBenchSource | 20.7% | — | Not comparable |
| OSWorld 2.0Source | 13.9% | 50.2% | GPT-5.6 Terra leads |
| Terminal-Bench 2.0Source | — | 87.4% | Not comparable |
| BrowseCompSource | — | 87.5% | Not comparable |
| CyberGymSource | — | 81.8% | Not comparable |
| ExploitGymSource | — | 23.2% | Not comparable |
| ToolathlonSource | — | 53.1% | Not comparable |
| AA Agentic IndexSource | — | 47.4% | Not comparable |
| GDPval-AASource | — | 54.1% | Not comparable |
| GDPval-AASource | — | 1581 | Not comparable |
| AA Harvey LABSource | — | 85.2% | Not comparable |
| AA ITBenchSource | — | 51.0% | Not comparable |
| AA Tau3 BankingSource | — | 31.8% | Not comparable |
| AA AutomationBenchSource | — | 45.6% | Not comparable |
| terminalBenchHardSource | — | 57.6% | Not comparable |
| aaTerminalBench21Source | — | 88% | Not comparable |
| APEX-Agents-AASource | — | 38.9% | Not comparable |
Coding10 benchmarks
| Benchmark | Claude Opus 4.7 | GPT-5.6 Terra | Result |
|---|---|---|---|
| Vibe Code BenchSource | 71.00% | — | Not comparable |
| React Native EvalsSource | 82.8% | — | Not comparable |
| AA-SciCodeSource | 50.1% | 53.9% | GPT-5.6 Terra leads |
| FrontierCode 1.1 MainSource | 38.5% | — | Not comparable |
| SWE-bench ProSource | — | 63.4% | Not comparable |
| Terminal-Bench 2.0Source | — | 87.4% | Not comparable |
| deepSweSource | — | 69.6% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 55.8% | Not comparable |
| cursorBench32Source | — | 64.9% | Not comparable |
| AA Coding IndexSource | — | 76.7% | Not comparable |
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude Opus 4.7 | GPT-5.6 Terra | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.7% | 55.0% | GPT-5.6 Terra leads |
| AA-GPQA DiamondSource | 88.5% | 92.5% | GPT-5.6 Terra leads |
| AA-HLESource | 31.2% | 41.8% | GPT-5.6 Terra leads |
| AA-Omniscience IndexSource | 14.2% | -0.2% | Claude Opus 4.7 leads |
| AA-Omniscience AccuracySource | 43.5% | 45.9% | GPT-5.6 Terra leads |
| AA-Omniscience Hallucination RateSource | 51.9% | 85.2% | Claude Opus 4.7 leads |
| GPQASource | — | 92.9% | Not comparable |
| GPQA-DSource | — | 92.9% | Not comparable |
| HealthBench ProfessionalSource | — | 57.7% | Not comparable |
| HealthBench HardSource | — | 32.7% | Not comparable |
MathGPT-5.6 Terra wins3 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 | GPT-5.6 Terra | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.6% | 71.2% | GPT-5.6 Terra leads |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 or GPT-5.6 Terra?
GPT-5.6 Terra is ahead on BenchLM's BenchAlign leaderboard, 72.57 to 71.94. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 22.917% and 68.300%.
Which is better for math, Claude Opus 4.7 or GPT-5.6 Terra?
GPT-5.6 Terra has the edge for math in this comparison, averaging 80.8 versus 38.6. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
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