Model comparison
GPT-5.2 vs Qwen3.6-35B-A3B
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GPT-5.2 #23; Qwen3.6-35B-A3B #31
BenchAlign evidence: GPT-5.2 estimated; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2 and Qwen3.6-35B-A3B share 18 comparable benchmark results. 5 of 8 categories are comparable. 11 results are unique to GPT-5.2; 40 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 18
- GPT-5.2 only
- 11
- Qwen3.6-35B-A3B only
- 40
- Comparable categories
- 5 / 8
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen3.6-35B-A3B only becomes the better choice if mathematics is the priority.
Confidence note. This is a partial-evidence comparison with 18 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-5.2 is clearly ahead on the provisional aggregate, 75 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 51.8. The single biggest benchmark swing on the page is SWE-bench Verified, 80% to 73.4%. Qwen3.6-35B-A3B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 gives you the larger context window at 400K, 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-5.2 | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Math | GPT-5.235.2 | Margin→ 53.0 | Qwen3.6-35B-A3B88.2 |
| Knowledge | GPT-5.292.4 | Margin← 40.6 | Qwen3.6-35B-A3B51.8 |
| Agentic | GPT-5.255.7 | Margin← 4.2 | Qwen3.6-35B-A3B51.5 |
| Multimodal | GPT-5.280.4 | Margin← 4.1 | Qwen3.6-35B-A3B76.3 |
| Coding | GPT-5.270.6 | Margin→ 3.2 | Qwen3.6-35B-A3B73.8 |
| Reasoning | GPT-5.252.9 | MarginNo overlap | Qwen3.6-35B-A3BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 80%B 73.4%Winner: GPT-5.2Δ 6.6SWE-bench Verified: GPT-5.2 scored 80%; Qwen3.6-35B-A3B scored 73.4%. GPT-5.2 wins this benchmark. - Source ↗
GPQA
KnowledgeA 92.4%B 86%Winner: GPT-5.2Δ 6.4GPQA: GPT-5.2 scored 92.4%; Qwen3.6-35B-A3B scored 86%. GPT-5.2 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 55.6%B 49.5%Winner: GPT-5.2Δ 6.1SWE-bench Pro: GPT-5.2 scored 55.6%; Qwen3.6-35B-A3B scored 49.5%. GPT-5.2 wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 79.5%B 75.3%Winner: GPT-5.2Δ 4.2MMMU-Pro: GPT-5.2 scored 79.5%; Qwen3.6-35B-A3B scored 75.3%. GPT-5.2 wins this benchmark. - Source ↗
CharXiv
MultimodalA 82.1%B 78%Winner: GPT-5.2Δ 4.1CharXiv: GPT-5.2 scored 82.1%; Qwen3.6-35B-A3B scored 78%. GPT-5.2 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.2 | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.273 tok/s | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2400K | Qwen3.6-35B-A3B262K | GPT-5.2 lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.2 wins18 benchmarks
| Benchmark | GPT-5.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| BrowseCompSource | 65.8% | — | Not comparable |
| OSWorld-VerifiedSource | 47.3% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | 95.3% | Qwen3.6-35B-A3B leads |
| Gert LabsSource | 46.54% | 42.65% | GPT-5.2 leads |
| JobBenchSource | 34.3% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | 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 |
| ToolathlonSource | — | 26.9% | Not comparable |
| MCP AtlasSource | — | 62.8% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
| AA Agentic IndexSource | — | 21.4% | Not comparable |
| GDPval-AASource | — | 27.4% | Not comparable |
| GDPval-AASource | — | 1049 | Not comparable |
CodingQwen3.6-35B-A3B wins10 benchmarks
| Benchmark | GPT-5.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80% | 73.4% | GPT-5.2 leads |
| SWE-bench ProSource | 55.6% | 49.5% | GPT-5.2 leads |
| Vibe Code BenchSource | 53.50% | — | Not comparable |
| Terminal-Bench HardSource | 47.0% | 34.8% | GPT-5.2 leads |
| AA-SciCodeSource | 52.1% | 35.8% | GPT-5.2 leads |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| LiveCodeBenchSource | — | 80.4% | Not comparable |
| NL2RepoSource | — | 29.4% | Not comparable |
| AA Coding IndexSource | — | 41.9% | Not comparable |
Reasoning3 benchmarks
KnowledgeGPT-5.2 wins11 benchmarks
| Benchmark | GPT-5.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| GPQASource | 92.4% | 86% | GPT-5.2 leads |
| Artificial Analysis Intelligence IndexSource | 42.2% | 31.6% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 90.3% | 84.1% | GPT-5.2 leads |
| AA-HLESource | 35.4% | 20.2% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -1.0% | -21.4% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 43.8% | 18.9% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 79.7% | 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-5.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA AIME 2025Source | 99.0% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 40.700% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 18.800% | — | 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-5.2 wins18 benchmarks
| Benchmark | GPT-5.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMMU-ProSource | 79.5% | 75.3% | GPT-5.2 leads |
| MathVisionSource | 83.0% | — | Not comparable |
| CharXivSource | 82.1% | 78% | GPT-5.2 leads |
| V*Source | 75.9% | — | Not comparable |
| Design Arena WebsiteSource | 1229 | — | Not comparable |
| MMMUSource | — | 81.7% | Not comparable |
| RealWorldQASource | — | 85.3% | Not comparable |
| OmniDocBench 1.5Source | — | 89.9% | 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 |
| AA-MMMU-ProSource | — | 75.0% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 64.4% | GPT-5.2 leads |
Frequently Asked Questions (6)
Which is better, GPT-5.2 or Qwen3.6-35B-A3B?
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 75 to 59. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 80% and 73.4%.
Which is better for knowledge tasks, GPT-5.2 or Qwen3.6-35B-A3B?
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 51.8. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.2 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for coding in this comparison, averaging 73.8 versus 70.6. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.2 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for math in this comparison, averaging 88.2 versus 35.2. GPT-5.2 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, GPT-5.2 or Qwen3.6-35B-A3B?
GPT-5.2 has the edge for agentic tasks in this comparison, averaging 55.7 versus 51.5. Inside this category, τ²-bench results is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.2 or Qwen3.6-35B-A3B?
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.4 versus 76.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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