Model comparison
DeepSeek V3.2 vs Qwen3.6-35B-A3B
Head-to-head evidence from 15 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: DeepSeek V3.2 unranked; Qwen3.6-35B-A3B #31
BenchAlign evidence: DeepSeek V3.2 supported; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and Qwen3.6-35B-A3B share 15 comparable benchmark results. 2 of 8 categories are comparable. 5 results are unique to DeepSeek V3.2; 43 to Qwen3.6-35B-A3B.
Updated July 15, 2026- Shared results
- 15
- DeepSeek V3.2 only
- 5
- Qwen3.6-35B-A3B only
- 43
- Comparable categories
- 2 / 8
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 5 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6-35B-A3B is clearly ahead on the provisional aggregate, 59 to 54. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-35B-A3B's sharpest advantage is in mathematics, where it averages 88.2 against 17.1.
Qwen3.6-35B-A3B is the reasoning model in the pair, while DeepSeek V3.2 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. Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 128K for DeepSeek V3.2.
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 | DeepSeek V3.2 | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Math | DeepSeek V3.217.1 | Margin→ 71.1 | Qwen3.6-35B-A3B88.2 |
| Coding | DeepSeek V3.260.9 | Margin→ 12.9 | Qwen3.6-35B-A3B73.8 |
| Agentic | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Knowledge | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.6-35B-A3B51.8 |
| Multimodal | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic15 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Claw-EvalSource | 40.2% | 68.7% | Qwen3.6-35B-A3B leads |
| VITA-BenchSource | 18.5% | 35.6% | Qwen3.6-35B-A3B leads |
| τ²-bench resultsSource | 78.9% | 95.3% | Qwen3.6-35B-A3B leads |
| Gert LabsSource | 29.57% | 42.65% | Qwen3.6-35B-A3B leads |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| τ³-bench resultsSource | — | 67.2% | 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 wins11 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-RebenchSource | 60.9% | — | Not comparable |
| React Native EvalsSource | 71.5% | — | Not comparable |
| Terminal-Bench HardSource | 32.6% | 34.8% | Qwen3.6-35B-A3B leads |
| AA-SciCodeSource | 38.7% | 35.8% | DeepSeek V3.2 leads |
| SWE-bench VerifiedSource | — | 73.4% | Not comparable |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| SWE-bench ProSource | — | 49.5% | 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 |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 31.6% | Qwen3.6-35B-A3B leads |
| AA-GPQA DiamondSource | 75.1% | 84.1% | Qwen3.6-35B-A3B leads |
| AA-HLESource | 10.5% | 20.2% | Qwen3.6-35B-A3B leads |
| AA-Omniscience IndexSource | -46.7% | -21.4% | Qwen3.6-35B-A3B leads |
| AA-Omniscience AccuracySource | 24.2% | 18.9% | DeepSeek V3.2 leads |
| AA-Omniscience Hallucination RateSource | 93.5% | 49.7% | Qwen3.6-35B-A3B leads |
| MMLU-ProSource | — | 85.2% | Not comparable |
| SuperGPQASource | — | 64.7% | Not comparable |
| C-EvalSource | — | 90% | Not comparable |
| GPQASource | — | 86% | Not comparable |
| HLESource | — | 21.4% | Not comparable |
MathQwen3.6-35B-A3B wins7 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 22.100% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.100% | — | 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 |
Multimodal16 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1208 | — | Not comparable |
| MMMUSource | — | 81.7% | Not comparable |
| MMMU-ProSource | — | 75.3% | 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 |
| AA-MMMU-ProSource | — | 75.0% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 49.0% | 64.4% | Qwen3.6-35B-A3B leads |
Frequently Asked Questions (3)
Which is better, DeepSeek V3.2 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 59 to 54.
Which is better for coding, DeepSeek V3.2 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for coding in this comparison, averaging 73.8 versus 60.9. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V3.2 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for math in this comparison, averaging 88.2 versus 17.1. DeepSeek V3.2 stays close enough that the answer can still flip depending on your workload.
Related Comparisons
Explore More
The AI models change fast. We track them for you.
A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.