Model comparison
Claude 4 Sonnet vs GPT-5.6 Sol
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude 4 Sonnet #158 (Supported); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude 4 Sonnet and GPT-5.6 Sol share 12 comparable benchmark results. 1 of 8 categories are comparable. 4 results are unique to Claude 4 Sonnet; 34 to GPT-5.6 Sol.
Updated July 23, 2026- Shared results
- 12
- Claude 4 Sonnet only
- 4
- GPT-5.6 Sol only
- 34
- Comparable categories
- 1 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Claude 4 Sonnet 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 12 shared benchmark results across 6 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 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 42.79. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $3.00 input / $15.00 output per 1M tokens for Claude 4 Sonnet. That is roughly 2.0x on output cost alone. GPT-5.6 Sol is the reasoning model in the pair, while Claude 4 Sonnet 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 4 Sonnet.
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 4 Sonnet | Δ | GPT-5.6 Sol |
|---|---|---|---|
| Coding | Claude 4 Sonnet72.7 | Margin← 8.1 | GPT-5.6 Sol64.6 |
| Agentic | Claude 4 SonnetNot measured | MarginNo overlap | GPT-5.6 Sol92.0 |
| Knowledge | Claude 4 SonnetNot measured | MarginNo overlap | GPT-5.6 Sol94.6 |
| Math | Claude 4 SonnetNot measured | MarginNo overlap | GPT-5.6 Sol87.5 |
| Multimodal | Claude 4 SonnetNot measured | MarginNo overlap | GPT-5.6 Sol83.0 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 4 Sonnet | GPT-5.6 Sol | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 4 Sonnet$3 input / $15 output | GPT-5.6 Sol$5 input / $30 output | Claude 4 Sonnet has the lower combined listed price. |
| Generation speedtokens per second | Claude 4 Sonnet40 tok/s | GPT-5.6 SolNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude 4 Sonnet1.33 s | GPT-5.6 SolNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude 4 Sonnet200K | GPT-5.6 Sol1M | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
Agentic19 benchmarks
| Benchmark | Claude 4 Sonnet | GPT-5.6 Sol | Result |
|---|---|---|---|
| τ²-bench resultsSource | 52.3% | 85.1% | GPT-5.6 Sol leads |
| Gert LabsSource | 39.66% | — | Not comparable |
| JobBenchSource | 18.4% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 91.9% | Not comparable |
| BrowseCompSource | — | 92.2% | Not comparable |
| OSWorld 2.0Source | — | 62.6% | Not comparable |
| CyberGymSource | — | 84.5% | Not comparable |
| ExploitGymSource | — | 33.7% | Not comparable |
| ToolathlonSource | — | 58% | 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 4 Sonnet wins9 benchmarks
| Benchmark | Claude 4 Sonnet | GPT-5.6 Sol | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 72.7% | — | Not comparable |
| AA-SciCodeSource | 37.3% | 56.1% | GPT-5.6 Sol leads |
| SWE-bench ProSource | — | 64.6% | Not comparable |
| 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 |
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude 4 Sonnet | GPT-5.6 Sol | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.5% | 58.9% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 68.3% | 94.1% | GPT-5.6 Sol leads |
| AA-HLESource | 4.0% | 47.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | -9.2% | 21.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 22.4% | 58.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 40.8% | 88.8% | Claude 4 Sonnet leads |
| GPQASource | — | 94.6% | Not comparable |
| GPQA-DSource | — | 94.6% | Not comparable |
| HealthBench ProfessionalSource | — | 60.5% | Not comparable |
| HealthBench HardSource | — | 33.1% | Not comparable |
Math3 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude 4 Sonnet | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA-IFBenchSource | 45.4% | 72.7% | GPT-5.6 Sol leads |
Frequently Asked Questions (2)
Which is better, Claude 4 Sonnet or GPT-5.6 Sol?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 42.79.
Which is better for coding, Claude 4 Sonnet or GPT-5.6 Sol?
Claude 4 Sonnet has the edge for coding in this comparison, averaging 72.7 versus 64.6. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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