Model comparison
GPT-5.6 Sol vs Qwen3.6 Plus
Head-to-head evidence from 23 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Qwen3.6 Plus #30 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Qwen3.6 Plus share 23 comparable benchmark results. 5 of 8 categories are comparable. 23 results are unique to GPT-5.6 Sol; 37 to Qwen3.6 Plus.
Updated July 23, 2026- Shared results
- 23
- GPT-5.6 Sol only
- 23
- Qwen3.6 Plus only
- 37
- Comparable categories
- 5 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Qwen3.6 Plus only becomes the better choice if coding is the priority.
Confidence note. This is a partial-evidence comparison with 23 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 65.2. 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 57.1. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 83.000% to 8.333%. Qwen3.6 Plus does hit back in coding, so the answer changes if that is the part of the workload you care about most.
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 | GPT-5.6 Sol | Δ | Qwen3.6 Plus |
|---|---|---|---|
| Knowledge | GPT-5.6 Sol94.6 | Margin← 37.5 | Qwen3.6 Plus57.1 |
| Agentic | GPT-5.6 Sol92.0 | Margin← 30.4 | Qwen3.6 Plus61.6 |
| Math | GPT-5.6 Sol87.5 | Margin← 27.0 | Qwen3.6 Plus60.5 |
| Coding | GPT-5.6 Sol64.6 | Margin→ 5.7 | Qwen3.6 Plus70.3 |
| Multimodal | GPT-5.6 Sol83.0 | Margin← 3.2 | Qwen3.6 Plus79.8 |
| Reasoning | GPT-5.6 SolNot measured | MarginNo overlap | Qwen3.6 Plus62.0 |
| Multilingual | GPT-5.6 SolNot measured | MarginNo overlap | Qwen3.6 Plus84.7 |
| Inst. Following | GPT-5.6 SolNot measured | MarginNo overlap | Qwen3.6 Plus82.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 83.000%B 8.333%Winner: GPT-5.6 SolΔ 74.7FrontierMath v2 (Tier 4): GPT-5.6 Sol scored 83.000%; Qwen3.6 Plus scored 8.333%. GPT-5.6 Sol wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 89.000%B 26.207%Winner: GPT-5.6 SolΔ 62.8FrontierMath v2 (Tiers 1-3): GPT-5.6 Sol scored 89.000%; Qwen3.6 Plus scored 26.207%. GPT-5.6 Sol wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 91.9%B 61.6%Winner: GPT-5.6 SolΔ 30.3Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Qwen3.6 Plus scored 61.6%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.6%B 56.6%Winner: GPT-5.6 SolΔ 8SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Qwen3.6 Plus scored 56.6%. GPT-5.6 Sol wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 83%B 78.8%Winner: GPT-5.6 SolΔ 4.2MMMU-Pro: GPT-5.6 Sol scored 83%; Qwen3.6 Plus scored 78.8%. 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 | GPT-5.6 Sol | Qwen3.6 Plus | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Qwen3.6 PlusNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Qwen3.6 PlusNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Qwen3.6 PlusNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Qwen3.6 Plus1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins27 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6 Plus | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | 61.6% | GPT-5.6 Sol leads |
| BrowseCompSource | 92.2% | — | Not comparable |
| OSWorld 2.0Source | 62.6% | — | Not comparable |
| CyberGymSource | 84.5% | — | Not comparable |
| ExploitGymSource | 33.7% | — | Not comparable |
| ToolathlonSource | 58% | 39.8% | GPT-5.6 Sol leads |
| AA Agentic IndexSource | 54.0% | 27.6% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 85.1% | 97.7% | Qwen3.6 Plus leads |
| GDPval-AASource | 61.8% | 31.8% | GPT-5.6 Sol leads |
| GDPval-AASource | 1736 | 1135 | GPT-5.6 Sol leads |
| 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 |
| Claw-EvalSource | — | 58.8% | Not comparable |
| QwenClawBenchSource | — | 57.2% | Not comparable |
| τ³-bench resultsSource | — | 70.7% | Not comparable |
| VITA-BenchSource | — | 44.3% | Not comparable |
| DeepPlanningSource | — | 41.5% | Not comparable |
| MCP AtlasSource | — | 48.2% | Not comparable |
| MCP-TasksSource | — | 74.1% | Not comparable |
| WideResearchSource | — | 74.3% | Not comparable |
| Gert LabsSource | — | 50.60% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
CodingQwen3.6 Plus wins12 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6 Plus | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | 56.6% | 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% | 54.5% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 56.1% | 40.7% | GPT-5.6 Sol leads |
| SWE-bench VerifiedSource | — | 78.8% | Not comparable |
| SWE MultilingualSource | — | 73.8% | Not comparable |
| LiveCodeBench v6Source | — | 87.1% | Not comparable |
| Vibe Code BenchSource | — | 25.56% | Not comparable |
Reasoning6 benchmarks
KnowledgeGPT-5.6 Sol wins15 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6 Plus | Result |
|---|---|---|---|
| GPQASource | 94.6% | 90.4% | GPT-5.6 Sol leads |
| GPQA-DSource | 94.6% | — | Not comparable |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | 39.6% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 94.1% | 88.2% | GPT-5.6 Sol leads |
| AA-HLESource | 47.2% | 25.7% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 21.7% | 2.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 58.5% | 26.2% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 88.8% | 32.0% | Qwen3.6 Plus leads |
| SuperGPQASource | — | 71.6% | Not comparable |
| MMLU-ProSource | — | 88.5% | Not comparable |
| MMLU-ReduxSource | — | 94.5% | Not comparable |
| C-EvalSource | — | 93.3% | Not comparable |
| HLESource | — | 28.8% | Not comparable |
MathGPT-5.6 Sol wins8 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6 Plus | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 89% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 89.000% | 26.207% | GPT-5.6 Sol leads |
| FrontierMath v2 (Tier 4)Source | 83.000% | 8.333% | GPT-5.6 Sol leads |
| AIME26Source | — | 95.3% | Not comparable |
| HMMT Feb 2025Source | — | 96.7% | Not comparable |
| HMMT Nov 2025Source | — | 94.6% | Not comparable |
| HMMT Feb 2026Source | — | 87.8% | Not comparable |
| MMAnswerBenchSource | — | 83.8% | Not comparable |
Multilingual2 benchmarks
MultimodalGPT-5.6 Sol wins10 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6 Plus | Result |
|---|---|---|---|
| MMMU-ProSource | 83% | 78.8% | GPT-5.6 Sol leads |
| MMMU-Pro w/ PythonSource | 84.6% | — | Not comparable |
| AA-MMMU-ProSource | 83.4% | 78.0% | GPT-5.6 Sol leads |
| MMMUSource | — | 86.0% | Not comparable |
| MathVisionSource | — | 88.0% | Not comparable |
| VideoMMMUSource | — | 84.0% | Not comparable |
| ScreenSpot ProSource | — | 68.2% | Not comparable |
| CharXivSource | — | 81.5% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| Design Arena WebsiteSource | — | 1249 | Not comparable |
Frequently Asked Questions (6)
Which is better, GPT-5.6 Sol or Qwen3.6 Plus?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 65.2. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 83.000% and 8.333%.
Which is better for knowledge tasks, GPT-5.6 Sol or Qwen3.6 Plus?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 57.1. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Sol or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for coding in this comparison, averaging 70.3 versus 64.6. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.6 Sol or Qwen3.6 Plus?
GPT-5.6 Sol has the edge for math in this comparison, averaging 87.5 versus 60.5. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.6 Sol or Qwen3.6 Plus?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 61.6. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.6 Sol or Qwen3.6 Plus?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 79.8. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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