Model comparison
GPT-5.6 Sol vs Qwen3.6-35B-A3B
Head-to-head evidence from 22 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Qwen3.6-35B-A3B #104 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Qwen3.6-35B-A3B share 22 comparable benchmark results. 5 of 8 categories are comparable. 24 results are unique to GPT-5.6 Sol; 35 to Qwen3.6-35B-A3B.
Updated July 23, 2026- Shared results
- 22
- GPT-5.6 Sol only
- 24
- Qwen3.6-35B-A3B only
- 35
- Comparable categories
- 5 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if coding is the priority.
Confidence note. This is a partial-evidence comparison with 22 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 51.47. 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 51.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 91.9% to 51.5%. Qwen3.6-35B-A3B 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 gives you the larger context window at 1M, compared with 262K for Qwen3.6-35B-A3B.
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 | Qwen3.6-35B-A3B |
|---|---|---|---|
| Knowledge | GPT-5.6 Sol94.6 | Margin← 43.2 | Qwen3.6-35B-A3B51.4 |
| Agentic | GPT-5.6 Sol92.0 | Margin← 40.5 | Qwen3.6-35B-A3B51.5 |
| Coding | GPT-5.6 Sol64.6 | Margin→ 9.2 | Qwen3.6-35B-A3B73.8 |
| Multimodal | GPT-5.6 Sol83.0 | Margin← 6.7 | Qwen3.6-35B-A3B76.3 |
| Math | GPT-5.6 Sol87.5 | Margin→ 0.7 | Qwen3.6-35B-A3B88.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 91.9%B 51.5%Winner: GPT-5.6 SolΔ 40.4Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Qwen3.6-35B-A3B scored 51.5%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.6%B 49.5%Winner: GPT-5.6 SolΔ 15.1SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Qwen3.6-35B-A3B scored 49.5%. GPT-5.6 Sol wins this benchmark. - Source ↗
GPQA
KnowledgeA 94.6%B 86%Winner: GPT-5.6 SolΔ 8.6GPQA: GPT-5.6 Sol scored 94.6%; Qwen3.6-35B-A3B scored 86%. GPT-5.6 Sol wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 83%B 75.3%Winner: GPT-5.6 SolΔ 7.7MMMU-Pro: GPT-5.6 Sol scored 83%; Qwen3.6-35B-A3B scored 75.3%. 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 | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Qwen3.6-35B-A3B262K | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins26 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | 51.5% | 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% | 26.9% | GPT-5.6 Sol leads |
| AA Agentic IndexSource | 54.0% | 21.4% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 85.1% | 95.3% | Qwen3.6-35B-A3B leads |
| GDPval-AASource | 61.8% | 27.4% | GPT-5.6 Sol leads |
| GDPval-AASource | 1736 | 1049 | 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 | — | 68.7% | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| τ³-bench resultsSource | — | 67.2% | Not comparable |
| VITA-BenchSource | — | 35.6% | Not comparable |
| DeepPlanningSource | — | 25.9% | Not comparable |
| MCP AtlasSource | — | 62.8% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
| Gert LabsSource | — | 42.65% | Not comparable |
CodingQwen3.6-35B-A3B wins12 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | 49.5% | GPT-5.6 Sol leads |
| Terminal-Bench 2.0Source | 91.9% | 51.5% | GPT-5.6 Sol leads |
| 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% | 41.9% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 56.1% | 35.8% | GPT-5.6 Sol leads |
| SWE-bench VerifiedSource | — | 73.4% | Not comparable |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| LiveCodeBenchSource | — | 80.4% | Not comparable |
| NL2RepoSource | — | 29.4% | Not comparable |
Reasoning4 benchmarks
KnowledgeGPT-5.6 Sol wins14 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| GPQASource | 94.6% | 86% | 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% | 31.6% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 94.1% | 84.1% | GPT-5.6 Sol leads |
| AA-HLESource | 47.2% | 20.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 21.7% | -21.4% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 58.5% | 18.9% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 88.8% | 49.7% | Qwen3.6-35B-A3B leads |
| MMLU-ProSource | — | 85.2% | Not comparable |
| SuperGPQASource | — | 64.7% | Not comparable |
| C-EvalSource | — | 90% | Not comparable |
| HLESource | — | 21.4% | Not comparable |
MathQwen3.6-35B-A3B wins8 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 89% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 89.000% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 83.000% | — | Not comparable |
| HMMT Feb 2025Source | — | 90.7% | Not comparable |
| HMMT Nov 2025Source | — | 89.1% | Not comparable |
| HMMT Feb 2026Source | — | 83.6% | Not comparable |
| MMAnswerBenchSource | — | 78.9% | Not comparable |
| AIME26Source | — | 92.7% | Not comparable |
MultimodalGPT-5.6 Sol wins16 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMMU-ProSource | 83% | 75.3% | GPT-5.6 Sol leads |
| MMMU-Pro w/ PythonSource | 84.6% | — | Not comparable |
| AA-MMMU-ProSource | 83.4% | 75.0% | GPT-5.6 Sol leads |
| MMMUSource | — | 81.7% | Not comparable |
| RealWorldQASource | — | 85.3% | Not comparable |
| OmniDocBench 1.5Source | — | 89.9% | Not comparable |
| CharXivSource | — | 78% | Not comparable |
| SimpleVQASource | — | 58.9% | Not comparable |
| CC-OCRSource | — | 81.9% | Not comparable |
| AI2D_TESTSource | — | 92.7% | Not comparable |
| RefCOCO (avg)Source | — | 92.0% | Not comparable |
| ODINW13Source | — | 50.8% | Not comparable |
| Video-MME (with subtitle)Source | — | 86.6% | Not comparable |
| Video-MME (w/o subtitle)Source | — | 82.5% | Not comparable |
| VideoMMMUSource | — | 83.7% | Not comparable |
| MLVU (M-Avg)Source | — | 86.2% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Sol | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.7% | 64.4% | GPT-5.6 Sol leads |
Frequently Asked Questions (6)
Which is better, GPT-5.6 Sol or Qwen3.6-35B-A3B?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 51.47. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 91.9% and 51.5%.
Which is better for knowledge tasks, GPT-5.6 Sol or Qwen3.6-35B-A3B?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 51.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Sol or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for coding in this comparison, averaging 73.8 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, GPT-5.6 Sol or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for math in this comparison, averaging 88.2 versus 87.5. GPT-5.6 Sol stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, GPT-5.6 Sol or Qwen3.6-35B-A3B?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 51.5. 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 Qwen3.6-35B-A3B?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 76.3. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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