Model comparison
GPT-5.2 vs Qwen3.5 397B
Head-to-head evidence from 20 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.2 #64 (Estimated); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2 and Qwen3.5 397B share 20 comparable benchmark results. 6 of 8 categories are comparable. 8 results are unique to GPT-5.2; 35 to Qwen3.5 397B.
Updated July 20, 2026- Shared results
- 20
- GPT-5.2 only
- 8
- Qwen3.5 397B only
- 35
- Comparable categories
- 6 / 8
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 6 evidence categories; 6 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 has the cleaner BenchAlign overall profile here, landing at 58.43 versus 57.01. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 56.6. The single biggest benchmark swing on the page is SWE-bench Pro, 55.6% to 50.9%. Qwen3.5 397B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. That is roughly 3.9x on output cost alone. GPT-5.2 is the reasoning model in the pair, while Qwen3.5 397B 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. GPT-5.2 gives you the larger context window at 400K, compared with 128K for Qwen3.5 397B.
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 | Qwen3.5 397B |
|---|---|---|---|
| Math | GPT-5.235.2 | Margin→ 55.4 | Qwen3.5 397B90.6 |
| Knowledge | GPT-5.292.4 | Margin← 35.8 | Qwen3.5 397B56.6 |
| Reasoning | GPT-5.252.9 | Margin→ 10.3 | Qwen3.5 397B63.2 |
| Coding | GPT-5.270.6 | Margin← 4.1 | Qwen3.5 397B66.5 |
| Multimodal | GPT-5.280.4 | Margin← 0.8 | Qwen3.5 397B79.6 |
| Agentic | GPT-5.255.7 | Margin→ 0.8 | Qwen3.5 397B56.5 |
| Multilingual | GPT-5.2Not measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Inst. Following | GPT-5.2Not measured | MarginNo overlap | Qwen3.5 397B92.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Pro
CodingA 55.6%B 50.9%Winner: GPT-5.2Δ 4.7SWE-bench Pro: GPT-5.2 scored 55.6%; Qwen3.5 397B scored 50.9%. GPT-5.2 wins this benchmark. - Source ↗
GPQA
KnowledgeA 92.4%B 88.4%Winner: GPT-5.2Δ 4GPQA: GPT-5.2 scored 92.4%; Qwen3.5 397B scored 88.4%. GPT-5.2 wins this benchmark. - Source ↗
BrowseComp
AgenticA 65.8%B 62%Winner: GPT-5.2Δ 3.8BrowseComp: GPT-5.2 scored 65.8%; Qwen3.5 397B scored 62%. GPT-5.2 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 80%B 76.2%Winner: GPT-5.2Δ 3.8SWE-bench Verified: GPT-5.2 scored 80%; Qwen3.5 397B scored 76.2%. GPT-5.2 wins this benchmark. - Source ↗
CharXiv
MultimodalA 82.1%B 80.8%Winner: GPT-5.2Δ 1.3CharXiv: GPT-5.2 scored 82.1%; Qwen3.5 397B scored 80.8%. 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 | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 output | Qwen3.5 397B$0.6 input / $3.6 output | Qwen3.5 397B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.273 tok/s | Qwen3.5 397B96 tok/s | Qwen3.5 397B has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | Qwen3.5 397B2.44 s | Qwen3.5 397B reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-5.2400K | Qwen3.5 397B128K | GPT-5.2 lists the larger context window. |
Benchmark Deep Dive
AgenticQwen3.5 397B wins20 benchmarks
| Benchmark | GPT-5.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| BrowseCompSource | 65.8% | 62% | GPT-5.2 leads |
| OSWorld-VerifiedSource | 47.3% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | 95.6% | Qwen3.5 397B leads |
| Gert LabsSource | 46.54% | 46.76% | Qwen3.5 397B leads |
| JobBenchSource | 34.3% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 52.5% | Not comparable |
| Claw-EvalSource | — | 56.8% | Not comparable |
| QwenClawBenchSource | — | 51.8% | Not comparable |
| τ³-bench resultsSource | — | 68.4% | Not comparable |
| VITA-BenchSource | — | 43.7% | 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 |
CodingGPT-5.2 wins6 benchmarks
ReasoningQwen3.5 397B wins5 benchmarks
KnowledgeGPT-5.2 wins12 benchmarks
| Benchmark | GPT-5.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| GPQASource | 92.4% | 88.4% | GPT-5.2 leads |
| Artificial Analysis Intelligence IndexSource | 42.2% | 33.7% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 90.3% | 89.3% | GPT-5.2 leads |
| AA-HLESource | 35.4% | 27.3% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -1.0% | -29.8% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 43.8% | 31.4% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 79.7% | 89.1% | GPT-5.2 leads |
| 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 wins8 benchmarks
| Benchmark | GPT-5.2 | Qwen3.5 397B | 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 |
| 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
MultimodalGPT-5.2 wins8 benchmarks
| Benchmark | GPT-5.2 | Qwen3.5 397B | Result |
|---|---|---|---|
| MMMU-ProSource | 79.5% | 79% | GPT-5.2 leads |
| MathVisionSource | 83.0% | 88.6% | Qwen3.5 397B leads |
| CharXivSource | 82.1% | 80.8% | GPT-5.2 leads |
| V*Source | 75.9% | 95.8% | Qwen3.5 397B leads |
| Design Arena WebsiteSource | 1227 | — | Not comparable |
| VideoMMMUSource | — | 84.7% | Not comparable |
| ScreenSpot ProSource | — | 65.6% | Not comparable |
| AA-MMMU-ProSource | — | 77.3% | Not comparable |
Frequently Asked Questions (7)
Which is better, GPT-5.2 or Qwen3.5 397B?
GPT-5.2 is ahead on BenchLM's BenchAlign leaderboard, 58.43 to 57.01. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 55.6% and 50.9%.
Which is better for knowledge tasks, GPT-5.2 or Qwen3.5 397B?
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 56.6. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.2 or Qwen3.5 397B?
GPT-5.2 has the edge for coding in this comparison, averaging 70.6 versus 66.5. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.2 or Qwen3.5 397B?
Qwen3.5 397B has the edge for math in this comparison, averaging 90.6 versus 35.2. GPT-5.2 stays close enough that the answer can still flip depending on your workload.
Which is better for reasoning, GPT-5.2 or Qwen3.5 397B?
Qwen3.5 397B has the edge for reasoning in this comparison, averaging 63.2 versus 52.9. Inside this category, CritPt is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.2 or Qwen3.5 397B?
Qwen3.5 397B has the edge for agentic tasks in this comparison, averaging 56.5 versus 55.7. 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 Qwen3.5 397B?
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.4 versus 79.6. Inside this category, V* is the benchmark that creates the most daylight between them.
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