Model comparison
DeepSeek V3.2 vs Qwen3.5 397B
Head-to-head evidence from 14 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 #82 (Supported); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 and Qwen3.5 397B share 14 comparable benchmark results. 2 of 8 categories are comparable. 5 results are unique to DeepSeek V3.2; 41 to Qwen3.5 397B.
Updated July 22, 2026- Shared results
- 14
- DeepSeek V3.2 only
- 5
- Qwen3.5 397B only
- 41
- Comparable categories
- 2 / 8
Pick Qwen3.5 397B if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 14 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
Qwen3.5 397B has the cleaner BenchAlign overall profile here, landing at 57.01 versus 55.4. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.5 397B's sharpest advantage is in mathematics, where it averages 90.6 against 17.1.
Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 8.6x on output cost alone.
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 | Qwen3.5 397B |
|---|---|---|---|
| Math | DeepSeek V3.217.1 | Margin→ 73.5 | Qwen3.5 397B90.6 |
| Coding | DeepSeek V3.260.9 | Margin→ 5.6 | Qwen3.5 397B66.5 |
| Agentic | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.5 397B56.5 |
| Reasoning | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Knowledge | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.5 397B56.6 |
| Multilingual | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.5 397B79.6 |
| Inst. Following | DeepSeek V3.2Not measured | MarginNo overlap | Qwen3.5 397B92.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2$0.28 input / $0.42 output | Qwen3.5 397B$0.6 input / $3.6 output | DeepSeek V3.2 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.235 tok/s | Qwen3.5 397B96 tok/s | Qwen3.5 397B has the higher measured throughput. |
| First-answer latencyseconds to first token | DeepSeek V3.23.75 s | Qwen3.5 397B2.44 s | Qwen3.5 397B reaches the first token sooner. |
| Context windowmaximum listed tokens | DeepSeek V3.2128K | Qwen3.5 397B128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| Claw-EvalSource | 40.2% | 56.8% | Qwen3.5 397B leads |
| VITA-BenchSource | 18.5% | 43.7% | Qwen3.5 397B leads |
| τ²-bench resultsSource | 78.9% | 95.6% | Qwen3.5 397B leads |
| Gert LabsSource | 29.57% | 46.76% | Qwen3.5 397B leads |
| Terminal-Bench 2.0Source | — | 52.5% | Not comparable |
| BrowseCompSource | — | 62% | Not comparable |
| QwenClawBenchSource | — | 51.8% | Not comparable |
| τ³-bench resultsSource | — | 68.4% | Not comparable |
| DeepPlanningSource | — | 37.6% | Not comparable |
| ToolathlonSource | — | 36.3% | Not comparable |
| MCP AtlasSource | — | 46.1% | Not comparable |
| MCP-TasksSource | — | 74.2% | Not comparable |
| WideResearchSource | — | 74.0% | Not comparable |
| ResearchClawBenchSource | — | 14.2% | Not comparable |
| AA Agentic IndexSource | — | 19.9% | Not comparable |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
| GDPval-AASource | — | 23.1% | Not comparable |
| GDPval-AASource | — | 962 | Not comparable |
CodingQwen3.5 397B wins7 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| SWE-RebenchSource | 60.9% | — | Not comparable |
| React Native EvalsSource | 71.5% | — | Not comparable |
| AA-SciCodeSource | 38.7% | 42.0% | Qwen3.5 397B leads |
| SWE-bench VerifiedSource | — | 76.2% | Not comparable |
| LiveCodeBench v6Source | — | 83.6% | Not comparable |
| SWE-bench ProSource | — | 50.9% | Not comparable |
| AA Coding IndexSource | — | 48.2% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 24.7% | 33.7% | Qwen3.5 397B leads |
| AA-GPQA DiamondSource | 75.1% | 89.3% | Qwen3.5 397B leads |
| AA-HLESource | 10.5% | 27.3% | Qwen3.5 397B leads |
| AA-Omniscience IndexSource | -46.7% | -29.8% | Qwen3.5 397B leads |
| AA-Omniscience AccuracySource | 24.2% | 31.4% | Qwen3.5 397B leads |
| AA-Omniscience Hallucination RateSource | 93.5% | 89.1% | Qwen3.5 397B leads |
| GPQASource | — | 88.4% | Not comparable |
| SuperGPQASource | — | 70.4% | Not comparable |
| MMLU-ProSource | — | 87.8% | Not comparable |
| MMLU-ReduxSource | — | 94.9% | Not comparable |
| C-EvalSource | — | 93% | Not comparable |
| HLESource | — | 28.7% | Not comparable |
MathQwen3.5 397B wins7 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 22.100% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.100% | — | Not comparable |
| AIME26Source | — | 93.3% | Not comparable |
| HMMT Feb 2025Source | — | 94.8% | Not comparable |
| HMMT Nov 2025Source | — | 92.7% | Not comparable |
| HMMT Feb 2026Source | — | 87.9% | Not comparable |
| MMAnswerBenchSource | — | 80.9% | Not comparable |
Multilingual2 benchmarks
Multimodal8 benchmarks
| Benchmark | DeepSeek V3.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1204 | — | Not comparable |
| MMMU-ProSource | — | 79% | Not comparable |
| MathVisionSource | — | 88.6% | Not comparable |
| CharXivSource | — | 80.8% | Not comparable |
| VideoMMMUSource | — | 84.7% | Not comparable |
| ScreenSpot ProSource | — | 65.6% | Not comparable |
| V*Source | — | 95.8% | Not comparable |
| AA-MMMU-ProSource | — | 77.3% | Not comparable |
Frequently Asked Questions (3)
Which is better, DeepSeek V3.2 or Qwen3.5 397B?
Qwen3.5 397B is ahead on BenchLM's BenchAlign leaderboard, 57.01 to 55.4.
Which is better for coding, DeepSeek V3.2 or Qwen3.5 397B?
Qwen3.5 397B has the edge for coding in this comparison, averaging 66.5 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 Qwen3.5 397B?
Qwen3.5 397B has the edge for math in this comparison, averaging 90.6 versus 17.1. DeepSeek V3.2 stays close enough that the answer can still flip depending on your workload.
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