Model comparison
DeepSeek V3.2 vs Qwen3.7 Max
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #82 (Supported); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and Qwen3.7 Max share 15 comparable benchmark results. 2 of 8 categories are comparable. 4 results are unique to DeepSeek V3.2; 43 to Qwen3.7 Max.
Updated July 23, 2026- Shared results
- 15
- DeepSeek V3.2 only
- 4
- Qwen3.7 Max only
- 43
- Comparable categories
- 2 / 8
Pick Qwen3.7 Max 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 6 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
Qwen3.7 Max is clearly ahead on the BenchAlign aggregate, 72.84 to 55.4. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.7 Max's sharpest advantage is in mathematics, where it averages 97.1 against 17.1.
Qwen3.7 Max 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. Qwen3.7 Max gives you the larger context window at 1M, 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 | Qwen3.7 Max |
|---|---|---|---|
| Math | DeepSeek V3.217.1 | Margin→ 80.0 | Qwen3.7 Max97.1 |
| Coding | DeepSeek V3.260.9 | Margin→ 17.0 | Qwen3.7 Max77.9 |
| Agentic | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.7 Max69.7 |
| Reasoning | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.7 Max90.4 |
| Knowledge | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.7 Max64.2 |
| Multilingual | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.7 Max87.0 |
| Inst. Following | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.7 Max84.4 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | Qwen3.7 Max | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | Qwen3.7 MaxNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | Qwen3.7 MaxNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | Qwen3.7 MaxNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | Qwen3.7 Max1M | Qwen3.7 Max lists the larger context window. |
Benchmark Deep Dive
Agentic21 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.7 Max | Result |
|---|---|---|---|
| Claw-EvalSource | 40.2% | 65.2% | Qwen3.7 Max leads |
| VITA-BenchSource | 18.5% | 47.9% | Qwen3.7 Max leads |
| τ²-bench resultsSource | 78.9% | 94.7% | Qwen3.7 Max leads |
| Gert LabsSource | 29.57% | 64.27% | Qwen3.7 Max leads |
| Terminal-Bench 2.0Source | — | 69.7% | Not comparable |
| QwenClawBenchSource | — | 64.3% | Not comparable |
| QwenWebBenchSource | — | 1568 | Not comparable |
| BFCL v4Source | — | 75.0% | Not comparable |
| MCP AtlasSource | — | 76.4% | Not comparable |
| HLE w/ toolsSource | — | 53.5% | Not comparable |
| AA Agentic IndexSource | — | 30.6% | Not comparable |
| GDPval-AASource | — | 38.7% | Not comparable |
| GDPval-AASource | — | 1273 | Not comparable |
| ResearchClawBenchSource | — | 18.7% | Not comparable |
| AA BriefcaseSource | — | 908 | Not comparable |
| AA AutomationBenchSource | — | 25.6% | Not comparable |
| AA EnterpriseOps-GymSource | — | 45.0% | Not comparable |
| AA ITBenchSource | — | 42.5% | Not comparable |
| terminalBenchHardSource | — | 50.8% | Not comparable |
| aaTerminalBench21Source | — | 74.5% | Not comparable |
| AA Harvey LABSource | — | 83.4% | Not comparable |
CodingQwen3.7 Max wins11 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.7 Max | Result |
|---|---|---|---|
| SWE-RebenchSource | 60.9% | — | Not comparable |
| React Native EvalsSource | 71.5% | — | Not comparable |
| AA-SciCodeSource | 38.7% | 48.8% | Qwen3.7 Max leads |
| SWE-bench VerifiedSource | — | 80.4% | Not comparable |
| SWE-bench ProSource | — | 60.6% | Not comparable |
| SWE MultilingualSource | — | 78.3% | Not comparable |
| NL2RepoSource | — | 47.2% | Not comparable |
| SciCodeSource | — | 53.5% | Not comparable |
| LiveCodeBenchSource | — | 91.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 69.7% | Not comparable |
| AA Coding IndexSource | — | 66.0% | Not comparable |
Reasoning3 benchmarks
Knowledge13 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.7 Max | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 46.0% | Qwen3.7 Max leads |
| AA-GPQA DiamondSource | 75.1% | 92.3% | Qwen3.7 Max leads |
| AA-HLESource | 10.5% | 38.1% | Qwen3.7 Max leads |
| AA-Omniscience IndexSource | -46.7% | 14.1% | Qwen3.7 Max leads |
| AA-Omniscience AccuracySource | 24.2% | 30.1% | Qwen3.7 Max leads |
| AA-Omniscience Hallucination RateSource | 93.5% | 22.9% | Qwen3.7 Max leads |
| GPQASource | — | 92.4% | Not comparable |
| GPQA-DSource | — | 92.4% | Not comparable |
| HLESource | — | 41.4% | Not comparable |
| MMLU-ProSource | — | 89.6% | Not comparable |
| MMLU-ReduxSource | — | 95% | Not comparable |
| SuperGPQASource | — | 73.6% | Not comparable |
| MMMLUSource | — | 90.3% | Not comparable |
MathQwen3.7 Max wins5 benchmarks
Multilingual5 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.7 Max | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1204 | 1293 | Qwen3.7 Max leads |
Frequently Asked Questions (3)
Which is better, DeepSeek V3.2 or Qwen3.7 Max?
Qwen3.7 Max is ahead on BenchLM's BenchAlign leaderboard, 72.84 to 55.4.
Which is better for coding, DeepSeek V3.2 or Qwen3.7 Max?
Qwen3.7 Max has the edge for coding in this comparison, averaging 77.9 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 Qwen3.7 Max?
Qwen3.7 Max has the edge for math in this comparison, averaging 97.1 versus 17.1. DeepSeek V3.2 stays close enough that the answer can still flip depending on your workload.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.