Model comparison
GPT-5.5 vs Qwen3.5 397B
Head-to-head evidence from 27 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.5 #9 (Estimated); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.5 and Qwen3.5 397B share 27 comparable benchmark results. 6 of 8 categories are comparable. 30 results are unique to GPT-5.5; 28 to Qwen3.5 397B.
Updated July 22, 2026- Shared results
- 27
- GPT-5.5 only
- 30
- Qwen3.5 397B only
- 28
- Comparable categories
- 6 / 8
Pick GPT-5.5 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 27 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-5.5 is clearly ahead on the BenchAlign aggregate, 73.51 to 57.01. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5's sharpest advantage is in agentic, where it averages 81.6 against 56.5. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 82% to 52.5%. 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-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. That is roughly 8.3x on output cost alone. GPT-5.5 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-5.5 gives you the larger context window at 1M, 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-5.5 | Δ | Qwen3.5 397B |
|---|---|---|---|
| Math | GPT-5.547.6 | Margin→ 43.0 | Qwen3.5 397B90.6 |
| Agentic | GPT-5.581.6 | Margin← 25.1 | Qwen3.5 397B56.5 |
| Reasoning | GPT-5.585.0 | Margin← 21.8 | Qwen3.5 397B63.2 |
| Multimodal | GPT-5.570.4 | Margin→ 9.2 | Qwen3.5 397B79.6 |
| Coding | GPT-5.558.6 | Margin→ 7.9 | Qwen3.5 397B66.5 |
| Knowledge | GPT-5.557.8 | Margin← 1.2 | Qwen3.5 397B56.6 |
| Multilingual | GPT-5.5Not measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Inst. Following | GPT-5.5Not measured | MarginNo overlap | Qwen3.5 397B92.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 82%B 52.5%Winner: GPT-5.5Δ 29.5Terminal-Bench 2.0: GPT-5.5 scored 82%; Qwen3.5 397B scored 52.5%. GPT-5.5 wins this benchmark. - Source ↗
HLE
KnowledgeA 52.2%B 28.7%Winner: GPT-5.5Δ 23.5HLE: GPT-5.5 scored 52.2%; Qwen3.5 397B scored 28.7%. GPT-5.5 wins this benchmark. - Source ↗
BrowseComp
AgenticA 84.4%B 62%Winner: GPT-5.5Δ 22.4BrowseComp: GPT-5.5 scored 84.4%; Qwen3.5 397B scored 62%. GPT-5.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 58.6%B 50.9%Winner: GPT-5.5Δ 7.7SWE-bench Pro: GPT-5.5 scored 58.6%; Qwen3.5 397B scored 50.9%. GPT-5.5 wins this benchmark. - Source ↗
GPQA
KnowledgeA 93.6%B 88.4%Winner: GPT-5.5Δ 5.2GPQA: GPT-5.5 scored 93.6%; Qwen3.5 397B scored 88.4%. GPT-5.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.5 | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.5$5 input / $30 output | Qwen3.5 397B$0.6 input / $3.6 output | Qwen3.5 397B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.5Not available | Qwen3.5 397B96 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.5Not available | Qwen3.5 397B2.44 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.51M | Qwen3.5 397B128K | GPT-5.5 lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.5 wins31 benchmarks
| Benchmark | GPT-5.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 82% | 52.5% | GPT-5.5 leads |
| CyberGymSource | 81.8% | — | Not comparable |
| BrowseCompSource | 84.4% | 62% | GPT-5.5 leads |
| OSWorld-VerifiedSource | 78.7% | — | Not comparable |
| MCP AtlasSource | 75.3% | 46.1% | GPT-5.5 leads |
| ToolathlonSource | 55.6% | 36.3% | GPT-5.5 leads |
| τ²-bench resultsSource | 93.9% | 95.6% | Qwen3.5 397B leads |
| AA Agentic IndexSource | 44.9% | 19.9% | GPT-5.5 leads |
| APEX-Agents-AASource | 37.7% | 15.3% | GPT-5.5 leads |
| GDPval-AASource | 49.5% | 23.1% | GPT-5.5 leads |
| GDPval-AASource | 1490 | 962 | GPT-5.5 leads |
| Gert LabsSource | 72.93% | 46.76% | GPT-5.5 leads |
| ResearchClawBenchSource | 17.0% | 14.2% | GPT-5.5 leads |
| OSWorld 2.0Source | 13.0% | — | Not comparable |
| JobBenchSource | 42.7% | — | Not comparable |
| ExploitGymSource | 13.4% | — | Not comparable |
| AA BriefcaseSource | 1154 | — | Not comparable |
| AA AutomationBenchSource | 42.1% | — | Not comparable |
| AA EnterpriseOps-GymSource | 46.6% | — | Not comparable |
| AA Harvey LABSource | 86.3% | — | Not comparable |
| AA ITBenchSource | 45.8% | — | Not comparable |
| AA Tau3 BankingSource | 31.3% | — | Not comparable |
| terminalBenchHardSource | 60.6% | — | Not comparable |
| aaTerminalBench21Source | 84.3% | — | 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 |
| MCP-TasksSource | — | 74.2% | Not comparable |
| WideResearchSource | — | 74.0% | Not comparable |
CodingQwen3.5 397B wins11 benchmarks
| Benchmark | GPT-5.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.6% | 50.9% | GPT-5.5 leads |
| Terminal-Bench 2.0Source | 82.0% | — | Not comparable |
| Vibe Code BenchSource | 69.85% | — | Not comparable |
| React Native EvalsSource | 84.7% | — | Not comparable |
| cursorBench31Source | 59.2% | — | Not comparable |
| cursorBench32Source | 58.4% | — | Not comparable |
| AA Coding IndexSource | 74.9% | 48.2% | GPT-5.5 leads |
| AA-SciCodeSource | 56.1% | 42.0% | GPT-5.5 leads |
| FrontierCode 1.1 MainSource | 43.0% | — | Not comparable |
| SWE-bench VerifiedSource | — | 76.2% | Not comparable |
| LiveCodeBench v6Source | — | 83.6% | Not comparable |
ReasoningGPT-5.5 wins7 benchmarks
| Benchmark | GPT-5.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| MRCR v2 64K-128KSource | 83.1% | — | Not comparable |
| MRCR v2 128K-256KSource | 87.5% | — | Not comparable |
| ARC-AGI-2Source | 85% | — | Not comparable |
| AA-LCRSource | 74.3% | 65.7% | GPT-5.5 leads |
| CritPtSource | 27.1% | 1.7% | GPT-5.5 leads |
| LongBench v2Source | — | 63.2% | Not comparable |
| AI-NeedleSource | — | 68.7% | Not comparable |
KnowledgeGPT-5.5 wins14 benchmarks
| Benchmark | GPT-5.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| GPQASource | 93.6% | 88.4% | GPT-5.5 leads |
| GPQA-DSource | 93.6% | — | Not comparable |
| HLESource | 52.2% | 28.7% | GPT-5.5 leads |
| HLE w/o toolsSource | 41.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 54.8% | 33.7% | GPT-5.5 leads |
| AA-GPQA DiamondSource | 93.5% | 89.3% | GPT-5.5 leads |
| AA-HLESource | 44.3% | 27.3% | GPT-5.5 leads |
| AA-Omniscience IndexSource | 20.1% | -29.8% | GPT-5.5 leads |
| AA-Omniscience AccuracySource | 56.9% | 31.4% | GPT-5.5 leads |
| AA-Omniscience Hallucination RateSource | 85.5% | 89.1% | GPT-5.5 leads |
| SuperGPQASource | — | 70.4% | Not comparable |
| MMLU-ProSource | — | 87.8% | Not comparable |
| MMLU-ReduxSource | — | 94.9% | Not comparable |
| C-EvalSource | — | 93% | Not comparable |
MathQwen3.5 397B wins8 benchmarks
| Benchmark | GPT-5.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 51.7% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 51.700% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 35.400% | — | 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
MultimodalQwen3.5 397B wins10 benchmarks
| Benchmark | GPT-5.5 | Qwen3.5 397B | Result |
|---|---|---|---|
| MMMU-ProSource | 81.2% | 79% | GPT-5.5 leads |
| MMMU-Pro w/ PythonSource | 83.2% | — | Not comparable |
| OfficeQA ProSource | 54.1% | — | Not comparable |
| AA-MMMU-ProSource | 79.9% | 77.3% | GPT-5.5 leads |
| Design Arena WebsiteSource | 1282 | — | 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 |
Frequently Asked Questions (7)
Which is better, GPT-5.5 or Qwen3.5 397B?
GPT-5.5 is ahead on BenchLM's BenchAlign leaderboard, 73.51 to 57.01. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 82% and 52.5%.
Which is better for knowledge tasks, GPT-5.5 or Qwen3.5 397B?
GPT-5.5 has the edge for knowledge tasks in this comparison, averaging 57.8 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-5.5 or Qwen3.5 397B?
Qwen3.5 397B has the edge for coding in this comparison, averaging 66.5 versus 58.6. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.5 or Qwen3.5 397B?
Qwen3.5 397B has the edge for math in this comparison, averaging 90.6 versus 47.6. GPT-5.5 stays close enough that the answer can still flip depending on your workload.
Which is better for reasoning, GPT-5.5 or Qwen3.5 397B?
GPT-5.5 has the edge for reasoning in this comparison, averaging 85 versus 63.2. Inside this category, CritPt is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.5 or Qwen3.5 397B?
GPT-5.5 has the edge for agentic tasks in this comparison, averaging 81.6 versus 56.5. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.5 or Qwen3.5 397B?
Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 70.4. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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