Model comparison
Claude Opus 4.8 vs GPT-5.6 Sol
Head-to-head evidence from 32 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.8 #5 (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 4.8 and GPT-5.6 Sol share 32 comparable benchmark results. 5 of 8 categories are comparable. 21 results are unique to Claude Opus 4.8; 14 to GPT-5.6 Sol.
Updated July 23, 2026- Shared results
- 32
- Claude Opus 4.8 only
- 21
- GPT-5.6 Sol only
- 14
- Comparable categories
- 5 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Claude Opus 4.8 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 32 shared benchmark results across 6 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 78.34. 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 mathematics, where it averages 87.5 against 53.9. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 31.250% to 83.000%. Claude Opus 4.8 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 4.8.
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 4.8 | Δ | GPT-5.6 Sol |
|---|---|---|---|
| Math | Claude Opus 4.853.9 | Margin→ 33.6 | GPT-5.6 Sol87.5 |
| Knowledge | Claude Opus 4.862.7 | Margin→ 31.9 | GPT-5.6 Sol94.6 |
| Coding | Claude Opus 4.881.1 | Margin← 16.5 | GPT-5.6 Sol64.6 |
| Agentic | Claude Opus 4.880.3 | Margin→ 11.7 | GPT-5.6 Sol92.0 |
| Multimodal | Claude Opus 4.877.0 | Margin→ 6.0 | GPT-5.6 Sol83.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 31.250%B 83.000%Winner: GPT-5.6 SolΔ 51.8FrontierMath v2 (Tier 4): Claude Opus 4.8 scored 31.250%; GPT-5.6 Sol scored 83.000%. GPT-5.6 Sol wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 47.241%B 89.000%Winner: GPT-5.6 SolΔ 41.8FrontierMath v2 (Tiers 1-3): Claude Opus 4.8 scored 47.241%; GPT-5.6 Sol scored 89.000%. GPT-5.6 Sol wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 74.6%B 91.9%Winner: GPT-5.6 SolΔ 17.3Terminal-Bench 2.0: Claude Opus 4.8 scored 74.6%; GPT-5.6 Sol scored 91.9%. GPT-5.6 Sol wins this benchmark. - Source ↗
BrowseComp
AgenticA 84.3%B 92.2%Winner: GPT-5.6 SolΔ 7.9BrowseComp: Claude Opus 4.8 scored 84.3%; GPT-5.6 Sol scored 92.2%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 69.2%B 64.6%Winner: Claude Opus 4.8Δ 4.6SWE-bench Pro: Claude Opus 4.8 scored 69.2%; GPT-5.6 Sol scored 64.6%. Claude Opus 4.8 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.8 | GPT-5.6 Sol | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.8$5 input / $25 output | GPT-5.6 Sol$5 input / $30 output | Claude Opus 4.8 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.8Not available | GPT-5.6 SolNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.8Not available | GPT-5.6 SolNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.81M | GPT-5.6 Sol1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins24 benchmarks
| Benchmark | Claude Opus 4.8 | GPT-5.6 Sol | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 74.6% | 91.9% | GPT-5.6 Sol leads |
| BrowseCompSource | 84.3% | 92.2% | GPT-5.6 Sol leads |
| DeepSearchQASource | 93.1% | — | Not comparable |
| OSWorld-VerifiedSource | 83.4% | — | Not comparable |
| Finance Agent v2Source | 53.9% | — | Not comparable |
| GDPval-AASource | 1594 | 1736 | GPT-5.6 Sol leads |
| MCP AtlasSource | 82.2% | — | Not comparable |
| ToolathlonSource | 59.9% | 58% | Claude Opus 4.8 leads |
| Gert LabsSource | 72.97% | — | Not comparable |
| AA Agentic IndexSource | 47.2% | 54.0% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 94.4% | 85.1% | Claude Opus 4.8 leads |
| GDPval-AASource | 54.7% | 61.8% | GPT-5.6 Sol leads |
| ResearchClawBenchSource | 21.1% | — | Not comparable |
| OSWorld 2.0Source | 20.6% | 62.6% | GPT-5.6 Sol leads |
| AA BriefcaseSource | 1347 | 1501 | GPT-5.6 Sol leads |
| AA AutomationBenchSource | 48.5% | 51.2% | GPT-5.6 Sol leads |
| AA EnterpriseOps-GymSource | 44.0% | — | Not comparable |
| AA Harvey LABSource | 91.1% | 87.2% | Claude Opus 4.8 leads |
| AA Tau3 BankingSource | 27.6% | 33.0% | GPT-5.6 Sol leads |
| terminalBenchHardSource | 58.3% | 65.9% | GPT-5.6 Sol leads |
| aaTerminalBench21Source | 84.6% | 88% | GPT-5.6 Sol leads |
| CyberGymSource | — | 84.5% | Not comparable |
| ExploitGymSource | — | 33.7% | Not comparable |
| AA ITBenchSource | — | 56.2% | Not comparable |
CodingClaude Opus 4.8 wins13 benchmarks
| Benchmark | Claude Opus 4.8 | GPT-5.6 Sol | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 88.6% | — | Not comparable |
| SWE-bench ProSource | 69.2% | 64.6% | Claude Opus 4.8 leads |
| SWE MultilingualSource | 84.4% | — | Not comparable |
| SWE MultimodalSource | 38.4% | — | Not comparable |
| Terminal-Bench 2.0Source | 74.6% | 91.9% | GPT-5.6 Sol leads |
| cursorBench31Source | 58.4% | — | Not comparable |
| cursorBench32Source | 62.3% | 67.2% | GPT-5.6 Sol leads |
| AA Coding IndexSource | 74.3% | 77.4% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 53.5% | 56.1% | GPT-5.6 Sol leads |
| FrontierCode 1.1 MainSource | 46.5% | — | Not comparable |
| deepSweSource | — | 72.7% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 60.6% | Not comparable |
| VulcanBench v3Source | — | 87.0% | Not comparable |
Reasoning4 benchmarks
KnowledgeGPT-5.6 Sol wins12 benchmarks
| Benchmark | Claude Opus 4.8 | GPT-5.6 Sol | Result |
|---|---|---|---|
| GPQASource | 93.6% | 94.6% | GPT-5.6 Sol leads |
| GPQA-DSource | 93.6% | 94.6% | GPT-5.6 Sol leads |
| HLESource | 57.9% | — | Not comparable |
| HLE w/o toolsSource | 49.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 55.7% | 58.9% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 92.0% | 94.1% | GPT-5.6 Sol leads |
| AA-HLESource | 45.7% | 47.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 27.4% | 21.7% | Claude Opus 4.8 leads |
| AA-Omniscience AccuracySource | 46.6% | 58.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 35.9% | 88.8% | Claude Opus 4.8 leads |
| HealthBench ProfessionalSource | — | 60.5% | Not comparable |
| HealthBench HardSource | — | 33.1% | Not comparable |
MathGPT-5.6 Sol wins4 benchmarks
Multilingual1 benchmarks
| Benchmark | Claude Opus 4.8 | GPT-5.6 Sol | Result |
|---|---|---|---|
| INCLUDESource | 87.6% | — | Not comparable |
MultimodalGPT-5.6 Sol wins8 benchmarks
| Benchmark | Claude Opus 4.8 | GPT-5.6 Sol | Result |
|---|---|---|---|
| OfficeQA ProSource | 66.2% | — | Not comparable |
| ScreenSpot ProSource | 87.9% | — | Not comparable |
| CharXivSource | 89.9% | — | Not comparable |
| CharXiv w/o toolsSource | 80.5% | — | Not comparable |
| Design Arena WebsiteSource | 1270 | — | Not comparable |
| MMMU-ProSource | — | 83% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 84.6% | Not comparable |
| AA-MMMU-ProSource | — | 83.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.8 | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA-IFBenchSource | 62.2% | 72.7% | GPT-5.6 Sol leads |
Frequently Asked Questions (6)
Which is better, Claude Opus 4.8 or GPT-5.6 Sol?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 78.34. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 31.250% and 83.000%.
Which is better for knowledge tasks, Claude Opus 4.8 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 62.7. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Opus 4.8 or GPT-5.6 Sol?
Claude Opus 4.8 has the edge for coding in this comparison, averaging 81.1 versus 64.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for math, Claude Opus 4.8 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for math in this comparison, averaging 87.5 versus 53.9. 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 4.8 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 80.3. Inside this category, AA Briefcase is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Claude Opus 4.8 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 77. Claude Opus 4.8 stays close enough that the answer can still flip depending on your workload.
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