Model comparison
Claude Opus 4.5 vs GPT-5.6 Sol
Head-to-head evidence from 20 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.5 #34 (Supported); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.5 and GPT-5.6 Sol share 20 comparable benchmark results. 5 of 8 categories are comparable. 39 results are unique to Claude Opus 4.5; 26 to GPT-5.6 Sol.
Updated July 23, 2026- Shared results
- 20
- Claude Opus 4.5 only
- 39
- GPT-5.6 Sol only
- 26
- Comparable categories
- 5 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Claude Opus 4.5 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 7 evidence categories; 5 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 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 64.22. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol's sharpest advantage is in knowledge, where it averages 94.6 against 58.1. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 4.167% to 83.000%. Claude Opus 4.5 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $5.00 input / $25.00 output per 1M tokens for Claude Opus 4.5. GPT-5.6 Sol is the reasoning model in the pair, while Claude Opus 4.5 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. GPT-5.6 Sol gives you the larger context window at 1M, compared with 200K for Claude Opus 4.5.
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 4.5 | Δ | GPT-5.6 Sol |
|---|---|---|---|
| Knowledge | Claude Opus 4.558.1 | Margin→ 36.5 | GPT-5.6 Sol94.6 |
| Math | Claude Opus 4.557.5 | Margin→ 30.0 | GPT-5.6 Sol87.5 |
| Agentic | Claude Opus 4.562.6 | Margin→ 29.4 | GPT-5.6 Sol92.0 |
| Multimodal | Claude Opus 4.569.9 | Margin→ 13.1 | GPT-5.6 Sol83.0 |
| Coding | Claude Opus 4.571.7 | Margin← 7.1 | GPT-5.6 Sol64.6 |
| Reasoning | Claude Opus 4.564.4 | MarginNo overlap | GPT-5.6 SolNot measured |
| Multilingual | Claude Opus 4.585.7 | MarginNo overlap | GPT-5.6 SolNot measured |
| Inst. Following | Claude Opus 4.569.5 | MarginNo overlap | GPT-5.6 SolNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 4.167%B 83.000%Winner: GPT-5.6 SolΔ 78.8FrontierMath v2 (Tier 4): Claude Opus 4.5 scored 4.167%; GPT-5.6 Sol scored 83.000%. GPT-5.6 Sol wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 20.690%B 89.000%Winner: GPT-5.6 SolΔ 68.3FrontierMath v2 (Tiers 1-3): Claude Opus 4.5 scored 20.690%; GPT-5.6 Sol scored 89.000%. GPT-5.6 Sol wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 59.3%B 91.9%Winner: GPT-5.6 SolΔ 32.6Terminal-Bench 2.0: Claude Opus 4.5 scored 59.3%; GPT-5.6 Sol scored 91.9%. GPT-5.6 Sol wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 70.6%B 83%Winner: GPT-5.6 SolΔ 12.4MMMU-Pro: Claude Opus 4.5 scored 70.6%; GPT-5.6 Sol scored 83%. GPT-5.6 Sol wins this benchmark. - Source ↗
GPQA
KnowledgeA 87%B 94.6%Winner: GPT-5.6 SolΔ 7.6GPQA: Claude Opus 4.5 scored 87%; GPT-5.6 Sol scored 94.6%. GPT-5.6 Sol wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.5 | GPT-5.6 Sol | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.5$5 input / $25 output | GPT-5.6 Sol$5 input / $30 output | Claude Opus 4.5 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.546 tok/s | GPT-5.6 SolNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.51.01 s | GPT-5.6 SolNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.5200K | GPT-5.6 Sol1M | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins29 benchmarks
| Benchmark | Claude Opus 4.5 | GPT-5.6 Sol | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.3% | 91.9% | GPT-5.6 Sol leads |
| OSWorld-VerifiedSource | 66.3% | — | Not comparable |
| OSWorldSource | 66.3% | — | Not comparable |
| Claw-EvalSource | 59.6% | — | Not comparable |
| QwenClawBenchSource | 52.3% | — | Not comparable |
| τ³-bench resultsSource | 70.2% | — | Not comparable |
| VITA-BenchSource | 23.3% | — | Not comparable |
| DeepPlanningSource | 26.4% | — | Not comparable |
| ToolathlonSource | 43.5% | 58% | GPT-5.6 Sol leads |
| MCP AtlasSource | 42.3% | — | Not comparable |
| MCP-TasksSource | 71.8% | — | Not comparable |
| WideResearchSource | 76.4% | — | Not comparable |
| CyberGymSource | 50.6% | 84.5% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 86.3% | 85.1% | Claude Opus 4.5 leads |
| Gert LabsSource | 64.23% | — | Not comparable |
| JobBenchSource | 32.3% | — | Not comparable |
| BrowseCompSource | — | 92.2% | Not comparable |
| OSWorld 2.0Source | — | 62.6% | Not comparable |
| ExploitGymSource | — | 33.7% | Not comparable |
| AA Agentic IndexSource | — | 54.0% | Not comparable |
| GDPval-AASource | — | 61.8% | Not comparable |
| GDPval-AASource | — | 1736 | Not comparable |
| AA BriefcaseSource | — | 1501 | Not comparable |
| AA ITBenchSource | — | 56.2% | Not comparable |
| AA Tau3 BankingSource | — | 33.0% | Not comparable |
| AA AutomationBenchSource | — | 51.2% | Not comparable |
| AA Harvey LABSource | — | 87.2% | Not comparable |
| terminalBenchHardSource | — | 65.9% | Not comparable |
| aaTerminalBench21Source | — | 88% | Not comparable |
CodingClaude Opus 4.5 wins12 benchmarks
| Benchmark | Claude Opus 4.5 | GPT-5.6 Sol | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.9% | — | Not comparable |
| LiveCodeBench v6Source | 84.8% | — | Not comparable |
| SWE-bench ProSource | 57.1% | 64.6% | GPT-5.6 Sol leads |
| SWE MultilingualSource | 77.5% | — | Not comparable |
| NL2RepoSource | 43.2% | — | Not comparable |
| AA-SciCodeSource | 47.0% | 56.1% | GPT-5.6 Sol leads |
| Terminal-Bench 2.0Source | — | 91.9% | Not comparable |
| deepSweSource | — | 72.7% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 60.6% | Not comparable |
| cursorBench32Source | — | 67.2% | Not comparable |
| VulcanBench v3Source | — | 87.0% | Not comparable |
| AA Coding IndexSource | — | 77.4% | Not comparable |
Reasoning6 benchmarks
KnowledgeGPT-5.6 Sol wins16 benchmarks
| Benchmark | Claude Opus 4.5 | GPT-5.6 Sol | Result |
|---|---|---|---|
| GPQASource | 87% | 94.6% | GPT-5.6 Sol leads |
| SuperGPQASource | 70.6% | — | Not comparable |
| MMLU-ProSource | 89.5% | — | Not comparable |
| MMLU-ReduxSource | 96.6% | — | Not comparable |
| C-EvalSource | 92.2% | — | Not comparable |
| HLESource | 30.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 34.7% | 58.9% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 81.0% | 94.1% | GPT-5.6 Sol leads |
| AA-HLESource | 12.9% | 47.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | -3.9% | 21.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 40.7% | 58.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 75.4% | 88.8% | Claude Opus 4.5 leads |
| AA MMLU-ProSource | 88.9% | — | Not comparable |
| GPQA-DSource | — | 94.6% | Not comparable |
| HealthBench ProfessionalSource | — | 60.5% | Not comparable |
| HealthBench HardSource | — | 33.1% | Not comparable |
MathGPT-5.6 Sol wins8 benchmarks
| Benchmark | Claude Opus 4.5 | GPT-5.6 Sol | Result |
|---|---|---|---|
| AIME26Source | 95.1% | — | Not comparable |
| HMMT Feb 2025Source | 92.9% | — | Not comparable |
| HMMT Nov 2025Source | 93.3% | — | Not comparable |
| HMMT Feb 2026Source | 85.3% | — | Not comparable |
| MMAnswerBenchSource | 84.0% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 20.690% | 89.000% | GPT-5.6 Sol leads |
| FrontierMath v2 (Tier 4)Source | 4.167% | 83.000% | GPT-5.6 Sol leads |
| FrontierMath (legacy)Source | — | 89% | Not comparable |
Multilingual2 benchmarks
MultimodalGPT-5.6 Sol wins9 benchmarks
| Benchmark | Claude Opus 4.5 | GPT-5.6 Sol | Result |
|---|---|---|---|
| MMMU-ProSource | 70.6% | 83% | GPT-5.6 Sol leads |
| MathVisionSource | 74.3% | — | Not comparable |
| CharXivSource | 68.5% | — | Not comparable |
| VideoMMMUSource | 84.4% | — | Not comparable |
| ScreenSpot ProSource | 45.7% | — | Not comparable |
| V*Source | 67.0% | — | Not comparable |
| AA-MMMU-ProSource | 71.2% | 83.4% | GPT-5.6 Sol leads |
| Design Arena WebsiteSource | 1277 | — | Not comparable |
| MMMU-Pro w/ PythonSource | — | 84.6% | Not comparable |
Frequently Asked Questions (6)
Which is better, Claude Opus 4.5 or GPT-5.6 Sol?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 64.22. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 4.167% and 83.000%.
Which is better for knowledge tasks, Claude Opus 4.5 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 58.1. Inside this category, AA-HLE is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Opus 4.5 or GPT-5.6 Sol?
Claude Opus 4.5 has the edge for coding in this comparison, averaging 71.7 versus 64.6. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, Claude Opus 4.5 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for math in this comparison, averaging 87.5 versus 57.5. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Claude Opus 4.5 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 62.6. Inside this category, CyberGym is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Claude Opus 4.5 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 69.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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