GPT-5.5 vs Qwen3.7
Full profiles: GPT-5.5 (OpenAI) and Qwen3.7 (Alibaba): every benchmark, price and rank.
Updated · Data from 13 sources
As of 29 Oct 2026, GPT-5.5 is ahead of Qwen3.7 on quality (64.4 vs 60.3 on the BenchLeader Index), but Qwen3.7 is 3.0× cheaper at $3.75 vs $11.25 per 1M tokens blended. Choose GPT-5.5 for agents & tools (62 vs 49), maths (70 vs 58), and long context (67 vs 64); choose Qwen3.7 for fast first answers (14.1 s vs 41.3 s) and instruction following (78 vs 74), where it also streams ~2× faster.
Key facts (as of 29 Oct 2026)
- GPT-5.5 scores 64.4 on the BenchLeader Index and Qwen3.7 scores 60.3 (BenchLeader, 29 Oct 2026).
- GPT-5.5 costs $11.25 per 1M tokens blended (list price, 29 Oct 2026).
- Qwen3.7 costs $3.75 per 1M tokens blended (list price, 29 Oct 2026).
- Qwen3.7 streams ~2× faster than GPT-5.5 (Artificial Analysis, 7-day median, 29 Oct 2026).
- Of the 54 benchmarks both models have, GPT-5.5 leads 47 (BenchLeader, 29 Oct 2026).
- On Arena WebDev, GPT-5.5 is rated 1512 and Qwen3.7 1515 (LMArena, as published by 29 Oct 2026).
GPT-5.5 benchmarks 
Qwen3.7 benchmarks Which to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | GPT-5.5 | 61 vs 59 category score; SciCode 55.8% vs 49.5% | Medium |
| Agents & tool use | GPT-5.5 | 62 vs 49 category score; τ³-Banking (AA) 39.0% vs 11.8% | High |
| Maths | GPT-5.5 | 70 vs 58 category score; FrontierMath Tiers 1–3 85.3% vs 64.6% | High |
| Reasoning | GPT-5.5 | 69 vs 66 category score; LiveBench 1.0 Reasoning 89.7% vs 83.3% | Medium |
| Knowledge | GPT-5.5 | 64 vs 61 category score; SimpleQA Verified 63.0% vs 55.8% | Medium |
| Long documents | GPT-5.5 | 67 vs 64 category score; AA-LCR v1.1 84.3% vs 79.0% | Medium |
| Following instructions | Qwen3.7 | 78 vs 74 category score; IFBench 80.5% vs 75.8% | Medium |
| Chat quality (human preference) | – | Only Qwen3.7 has an Arena rating (56 category score) | Not comparable |
| Lowest cost | Qwen3.7 | $3.75 vs $11.25 per 1M blended; agentic coding session $0.180 vs $0.420 | – |
| Fastest first answer | Qwen3.7 | 14.1 s (Qwen3.7 (max)) vs 41.3 s (GPT-5.5 (xhigh)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GPT-5.5 (xhigh) leads on quality: 64.4 vs 60.3.
- GPT-5.5 (xhigh) is stronger in agents & tools, coding, knowledge, long context, maths, multimodal, reasoning.
- Qwen3.7 (max) is stronger in instruction following, human preference.
- Qwen3.7 (max) is 3.0× cheaper ($3.75 vs $11.25 per 1M blended).
- Qwen3.7 (max) streams 2.3× faster (201 vs 87 tokens per second).
At a glance
| Spec | GPT-5.5 | Qwen3.7 |
|---|---|---|
| Developer | OpenAI | Alibaba |
| Released | 23 Apr 2026 | 19 May 2026 |
| Context window (tokens) | 1,050,000 | 1,000,000 |
| Compared at | GPT-5.5 (xhigh) | Qwen3.7 (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $5.00 / $30.00 / $0.500 | $2.50 / $7.50 / $0.500 |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | GPT-5.5 (xhigh) | Qwen3.7 (max) | Leader |
|---|---|---|---|
| Reasoning | 68.9 | 66.2 | GPT-5.5 |
| Coding | 60.9 | 59.1 | GPT-5.5 |
| Agents & tools | 62.3 | 49.3 | GPT-5.5 |
| Maths | 69.6 | 58.1 | GPT-5.5 |
| Knowledge | 63.7 | 61.2 | GPT-5.5 |
| Instruction following | 73.9 | 78.0 | Qwen3.7 |
| Human preference | – | 55.6 | not comparable |
| Multimodal | 62.6 | – | not comparable |
| Long context | 67.1 | 64.3 | GPT-5.5 |
Where sources disagree
Across the 54 benchmarks both have, GPT-5.5 leads 47, Qwen3.7 leads 7. Every overall index that rates both puts GPT-5.5 ahead.
| Overall index | GPT-5.5 (xhigh) | Qwen3.7 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 64.4 | 60.3 | GPT-5.5 |
| Arena Text | 1482† | 1474 | GPT-5.5 |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | GPT-5.5 (xhigh) | Qwen3.7 (max) |
|---|---|---|
| Blended price per 1M tokens | $11.25 | $3.75 |
| Input / output per 1M | $5.00 / $30.00 | $2.50 / $7.50 |
| Cached input per 1M | $0.500 | $0.500 |
| Price per task: chat reply | $0.011 | $0.0033 |
| Price per task: summarize a 30-page report | $0.078 | $0.035 |
| Price per task: code edit | $0.075 | $0.026 |
| Price per task: agentic coding session | $0.420 | $0.180 |
| Price per task: structured extraction | $0.016 | $0.0065 |
| Output speed | 87 tok/s | 201 tok/s |
| Time to first answer | 41.3 s | 14.1 s |
| Time to a complete answer | 47.1 s | 16.6 s |
Each model is compared at its best-ranked reasoning-effort setting. GPT-5.5 (xhigh) scores 64.4 and takes 41 s to its first answer token; GPT-5.5 (high) scores 63.7 in 16 s, GPT-5.5 scores 61.7 in 3 s. Qwen3.7 (max) scores 60.3 and takes 14 s to its first answer token. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
124 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | GPT-5.5 (xhigh) | Qwen3.7 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 64.4 | 60.3 |
| Agents & tools score | BenchLeader | 62.3 | 49.3 |
| Coding score | BenchLeader | 60.9 | 59.1 |
| Instruction following score | BenchLeader | 73.9 | 78.0 |
| Knowledge score | BenchLeader | 63.7 | 61.2 |
| Long context score | BenchLeader | 67.1 | 64.3 |
| Maths score | BenchLeader | 69.6 | 58.1 |
| Multimodal score | BenchLeader | 62.6 | – |
| Reasoning score | BenchLeader | 68.9 | 66.2 |
| Human preference score | BenchLeader | – | 55.6 |
| Blended price $/M | BenchLeader | $11.25 | $3.75 |
| Output speed | BenchLeader | 87 tok/s | 201 tok/s |
| Time to first answer | BenchLeader | 41.3 s | 14.1 s |
| Context window | BenchLeader | 1,050,000 tokens | 1,000,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 90.7%† | 90.9% |
| SimpleBench | SimpleBench | 69.0%† | 70.4% |
| Arena Hard Prompts | Arena (LMArena) | 1499† | 1495 |
| LiveBench 1.0 Reasoning | LiveBench | 89.7% | 83.3% |
| GPQA Diamond (AA) | Artificial Analysis | 93.5% | 92.3% |
| Humanity's Last Exam (AA) | Artificial Analysis | 45.8% | 40.5% |
| GPQA Diamond (Vals) | Vals AI | 93.2% | 90.2% |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 88.8%† | – |
| ARC-AGI-1 | ARC Prize | 95.0% | – |
| ARC-AGI-2 | ARC Prize | 85.0% | – |
| ARC-AGI-3 | ARC Prize | 0.4%† | – |
| CritPt | Artificial Analysis | 27.1% | 13.4% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 63.0% | 26.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 56.0% | 32.0% |
| CL-bench Life | Epoch AI Benchmarking Hub | 22.2%† | – |
| LMCA | Epoch AI Benchmarking Hub | 54.3% | 44.0% |
| DTBench | Epoch AI Benchmarking Hub | 96.0% | 92.3% |
| ForecastBench | ForecastBench | 64.5%† | – |
| BTF-3 | Epoch AI Benchmarking Hub | 14.3%† | – |
| Coding | |||
| SWE-bench Verified (Epoch) | Epoch AI Benchmarking Hub | – | 77.3% |
| SciCode | SciCode | 55.8% | 49.5% |
| WeirdML | WeirdML | 84.9% | – |
| FrontierCode | Cognition | 43.0%† | – |
| GSO-Bench | GSO-Bench | 40.2% | – |
| Arena Coding | Arena (LMArena) | 1510† | 1523 |
Show all 124 benchmarks
| Metric | Publisher | GPT-5.5 (xhigh) | Qwen3.7 (max) |
|---|---|---|---|
| Coding | |||
| Arena WebDev | Arena (LMArena) | 1512 | 1515 |
| LiveBench 1.0 Coding | LiveBench | 82.2% | 74.2% |
| LiveCodeBench | Vals AI | 85.3% | 87.1% |
| SWE-bench (Vals) | Vals AI | 82.6% | 68.8% |
| Code Migration | Vals AI | 45.2% | 13.1% |
| ProgramBench | Vals AI | 0.5% | – |
| Vibe Code Bench v1.1 | Vals AI | 69.8% | 47.7% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 45.4% | – |
| SWE Atlas: Refactoring | Scale AI SEAL | 44.8% | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 42.6% | – |
| MirrorCode | Epoch AI Benchmarking Hub | 10.0%† | – |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 88.1%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 67.0% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 1943.0 | 1189.4 |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 14.7% | 1.5% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 84.3% | 74.5% |
| Startrise Frontend | Startrise | – | 63.6% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 84.7%† | – |
| OSWorld-Verified 2.0 | OSWorld | 13.0% | – |
| Remote Labor Index | Scale AI / CAIS | 6.3%† | – |
| APEX-Agents | Mercor | 55.1%† | – |
| Arena Agent | Arena (LMArena) | – | -6.6 |
| LiveBench Agentic Coding | LiveBench | 54.0% | 43.6% |
| Terminal-Bench Hard | Artificial Analysis | 60.6% | 50.8% |
| τ²-Bench Telecom (AA) | Artificial Analysis | 93.9% | 94.7% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 76.4%† | 61.0% |
| MCP Atlas | Scale AI SEAL | 75.3% | – |
| HiL-Bench | Scale AI SEAL | 39.7%† | – |
| τ³-bench Banking | τ²-bench | 44.6% | – |
| τ³-Banking (AA) | Artificial Analysis | 39.0% | 11.8% |
| ITBench SRE (AA) | Artificial Analysis | 45.8% | 42.5% |
| Analyst Agent (AA) | Artificial Analysis | 50.0% | 18.8% |
| APEX-Agents (AA) | Artificial Analysis | 37.7% | – |
| Finance Agent v2 | Vals AI | 51.8% | 47.8% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 3.8% | 1.7% |
| Legal Research Bench | Vals AI | 40.4% | 25.5% |
| SkillsBench | Vals AI | 62.2% | – |
| SREBench | Vals AI | 3.8% | – |
| Tax Agent Bench | Vals AI | 21.8% | 15.8% |
| Terminal-Bench 2.0 (Vals) | Vals AI | 73.2%† | 59.2% |
| Time Horizon Index: KSP | Vals AI | 8.3% | – |
| DeepResearch Bench | DeepResearch Bench | 54.0%† | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 27.2% | – |
| ExploitBench | Epoch AI Benchmarking Hub | 47.4%† | – |
| GBAEval | Epoch AI Benchmarking Hub | 53.2%† | 0.4% |
| Vending-Bench 2 | Andon Labs | 7523.8† | – |
| AutomationBench | Artificial Analysis | 47.3% | 23.0% |
| GDP.pdf (AA) | Artificial Analysis | 21.2% | 8.6% |
| EnterpriseOps-Gym | Artificial Analysis | 46.6% | 45.0% |
| AA-Briefcase v1.1 | Artificial Analysis | 1136 | 917 |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 85.3% | 64.6% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 72.5% | 34.1% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 84.4%† | 95.6% |
| ProofBench | Vals AI | 50.0% | 26.0% |
| LiveBench Mathematics | LiveBench | 95.9% | 85.3% |
| AIME 2026 | MathArena | 100.0% | – |
| HMMT February 2026 | MathArena | 98.5% | – |
| USAMO 2026 | MathArena | 98.2% | – |
| MathArena Apex | MathArena | 80.2% | – |
| Arena Maths | Arena (LMArena) | 1500† | 1482 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 63.0% | 55.8% |
| LiveBench 1.0 Data Analysis | LiveBench | 81.6% | 71.8% |
| MMLU-Pro | Vals AI | 88.1% | 89.3% |
| LegalBench | Vals AI | 86.5% | 84.9% |
| CorpFin | Vals AI | 68.4% | 63.7% |
| TaxEval | Vals AI | 75.0% | 75.3% |
| CaseLaw v2 | Vals AI | 66.2% | – |
| Excel Modeling Benchmark | Vals AI | 64.5% | 57.0% |
| MedCode | Vals AI | 49.1% | 38.8% |
| MedScribe | Vals AI | 86.9% | 79.4% |
| Public Benefits Bench v1.1 | Vals AI | 60.9% | – |
| DrugDiscoveryBench | Scale AI SEAL | 51.6% | 29.3%† |
| EBR-bench | Epoch AI Benchmarking Hub | 34.3% | 9.5% |
| GDP.pdf | Epoch AI Benchmarking Hub | 26.0% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 87.4% | 79.7% |
| LiveBench Instruction Following | LiveBench | 70.7% | 74.0% |
| IFBench | Artificial Analysis | 75.8% | 80.5% |
| Arena Instruction Following | Arena (LMArena) | 1475† | 1465 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1477† | 1474 |
| EQ-Bench 4 | EQ-Bench | 1295† | 1100 |
| Arena Creative Writing | Arena (LMArena) | 1448† | 1437 |
| Arena Multi-turn | Arena (LMArena) | 1484† | 1482 |
| Arena Longer Queries | Arena (LMArena) | 1487† | 1490 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1297† | – |
| MMMU-Pro | Artificial Analysis | 79.9% | – |
| MMMU-Pro (Vals) | Vals AI | 88.3% | – |
| MortgageTax | Vals AI | 68.8% | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 36.2%† | – |
| Code2Video-AA | Artificial Analysis | 1000 | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 84.3% | 79.0% |
| Arena Document | Arena (LMArena) | 1483† | – |
| MLCR | Artificial Analysis | 28.9% | 14.4% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 159.6† | 154.1 |
| LiveBench 1.0 | LiveBench | 80.2% | 73.1% |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 38.4 | 29.5 |
| AA Progress Index v1 | Artificial Analysis | 320 | 293.8 |
| Vals RSI Index | Vals AI | 16.5% | – |
| Vals Multimodal Index | Vals AI | 68.1% | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 16.3% | – |
Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.
What changed
- GPT-5.5 (xhigh): 1 new result (Code2Video-AA).
- Qwen3.7 (max): BenchLeader Index 60.8 → 60.3.
- GPT-5.5 (xhigh): 1 new result (AA Progress Index v1).
- Qwen3.7 (max): 1 new result (AA Progress Index v1).
- Qwen3.7 (max): cached input price moved from $0.33/M to $0.50/M (52% up).
- GPT-5.5 (xhigh): cost per task moved from $2.63/M to $2.10/M (20% down).
- Qwen3.7 (max): cost per task moved from $1.15/M to $0.93/M (19% down).
- GPT-5.5 (xhigh): 1 new result (AA-Briefcase v1.1).
- Qwen3.7 (max): 1 new result (AA-Briefcase v1.1); 1 score revision; cached input price moved from $0.50/M to $0.33/M (34% down).
- Qwen3.7 (max): cached input price moved from $0.33/M to $0.50/M (52% up).
Related comparisons
- GPT-5.5 vs Claude Opus 5.5
- GPT-5.5 vs Gemini 4 Carbon
- GPT-5.5 vs GPT-6 Astra
- Qwen3.7 vs Claude Opus 5.5
- Qwen3.7 vs Gemini 4 Carbon
- Qwen3.7 vs GPT-6 Astra
- Qwen3.7 vs GPT-6.1 Sol
- GPT-5.4 vs Qwen3.7
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GPT-5.5 vs Qwen3.7: questions
- Is GPT-5.5 better than Qwen3.7?
- GPT-5.5 (xhigh) leads on quality: 64.4 vs 60.3. The BenchLeader Index combines every independent quality benchmark; GPT-5.5 (xhigh) is ahead overall as of 29 Oct 2026, but check the category scores for your use.
- GPT-5.5 vs Qwen3.7: which is cheaper, and will that change?
- Qwen3.7 is cheaper today: $3.75 against $11.25 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GPT-5.5 or Qwen3.7 better for coding?
- GPT-5.5 scores higher in coding (61 vs 59 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1512 for GPT-5.5 against 1515 for Qwen3.7.
- Which is faster, GPT-5.5 or Qwen3.7?
- Qwen3.7 streams ~2× faster (201 vs 87 output tokens per second, Artificial Analysis 7-day median).
- Is GPT-5.5 or Qwen3.7 better for agents and tool use?
- GPT-5.5 scores higher in agentic tasks (62 vs 49 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 39.0% for GPT-5.5 against 11.8% for Qwen3.7.
More questions (4)
- Which is better for long documents?
- GPT-5.5 scores higher on long-context benchmarks (67 vs 64). Both take about 1.1M tokens: GPT-5.5 1,050,000, Qwen3.7 1,000,000.
- Which has lower latency?
- Qwen3.7 answers first: 14.1 s against 41.3 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Do independent benchmarks agree on GPT-5.5 vs Qwen3.7?
- Across the 54 benchmarks both have, GPT-5.5 leads 47, Qwen3.7 leads 7. Every overall index that rates both puts GPT-5.5 ahead.
- When was Qwen3.7 released?
- Qwen3.7 was released on 19 May 2026.