Model comparison
GPT-4.1 vs Qwen3.7 Max
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 35.9 on the Noometry Index.
Last verified . 23 shared benchmarks.
Alibaba (Qwen)Summary
- They share 23 benchmarks with published results for both. GPT-4.1 scores higher in 1 category and Qwen3.7 Max in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.7 Max leads 62.4 to 22.3.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 6% for GPT-4.1 and 64.6% for Qwen3.7 Max.
- GPT-4.1 is cheaper at $2 / $8 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- GPT-4.1 accepts more context: 1.05M tokens versus 1M.
Side by side
| GPT-4.1 | Qwen3.7 Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 35.9 | 51.5 |
| Released | 2025-04-14 | 2026-05-19 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1M |
| Max output | 33K | 131K |
| Input $ / M tokens | $2 | $2.50 |
| Output $ / M tokens | $8 | $7.50 |
| Results tracked | 52 | 33 |
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Category by category
Coding Qwen3.7 Max leads
GPT-4.1: 34.4 (#238), Qwen3.7 Max: 50.4 (#45)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| SWE-bench Verified | 48.5% | 77.3% |
| LMArena Coding | 1391 | 1498 |
| ALE-Bench | 558.1 | 1,189 |
| SWE-bench Verified (bash only) | 39.6% | — |
| Aider Polyglot | 52.4% | — |
| LMArena WebDev | — | 1515 |
| SciCode | — | 48.8% |
| WeirdML | 39% | — |
| CadEval | 42% | — |
Agentic & Tool Use GPT-4.1 leads
GPT-4.1: 34.7 (#43), Qwen3.7 Max: 22.1 (#135)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | — |
| GBAEval | — | 0.4% |
Reasoning Qwen3.7 Max leads
GPT-4.1: 11.7 (#339), Qwen3.7 Max: 49.2 (#38)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| SimpleBench | 27% | 70.4% |
| Chess Puzzles | 6% | 19% |
| LMArena Hard Prompts | 1384 | 1483 |
| DTBench | 68.3% | 92.3% |
| LMCA | 25.6% | 44% |
| Epoch Capabilities Index | 136.78 | 153.68 |
| ARC-AGI-2 | 0.4% | — |
| Kagi LLM Benchmark | 52.3% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 5.5% | — |
| CritPt | — | 13.4% |
| EnigmaEval | 2.2% | — |
| EBR-Bench | — | 9.5% |
| Mystery Game Puzzles | — | 32% |
| ForecastBench | 61.5 | — |
Math Qwen3.7 Max leads
GPT-4.1: 22.3 (#280), Qwen3.7 Max: 62.4 (#32)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6% | 64.6% |
| OTIS Mock AIME 2024-2025 | 38.3% | 95.6% |
| LMArena Math | 1370 | 1490 |
| FrontierMath Tier 4 | — | 34.1% |
| ProofBench | — | 26% |
| Omni-MATH | 47.1% | — |
| MATH Level 5 | 83% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3.7 Max leads
GPT-4.1: 37.1 (#160), Qwen3.7 Max: 61.6 (#28)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| GPQA Diamond | 66.9% | 90.9% |
| SimpleQA Verified | 31.1% | 55.8% |
| LMArena Expert | 1364 | 1488 |
| Humanity's Last Exam | 5.4% | — |
| MMLU-Pro | 81.1% | — |
| Vectara Hallucination Rate | 5.6% | — |
| GPQA (HELM) | 65.9% | — |
Multimodal Not comparable
GPT-4.1: 38.2 (#67), Qwen3.7 Max: —
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| LMArena Vision | 1211 | — |
| GeoBench | 72% | — |
Multilingual Qwen3.7 Max leads
GPT-4.1: 49.4 (#133), Qwen3.7 Max: 56.9 (#15)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1370 | 1474 |
| LMArena Chinese | 1382 | 1530 |
| LMArena Russian | 1377 | 1484 |
| LMArena French | 1382 | — |
| LMArena German | 1381 | — |
| LMArena Japanese | 1319 | — |
| LMArena Korean | 1339 | — |
| LMArena Spanish | 1376 | — |
Instruction Following Qwen3.7 Max leads
GPT-4.1: 71.3 (#153), Qwen3.7 Max: 76.7 (#38)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1367 | 1460 |
| IFEval | 83.8% | — |
Long Context Qwen3.7 Max leads
GPT-4.1: 40.0 (#163), Qwen3.7 Max: 45.4 (#40)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1385 | 1482 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference Qwen3.7 Max leads
GPT-4.1: 57.6 (#125), Qwen3.7 Max: 65.0 (#54)
| Benchmark | GPT-4.1 | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1383 | 1476 |
| LMArena Creative Writing | 1363 | 1449 |
| LMArena Multi-Turn | 1398 | 1481 |
| EQ-Bench Creative Writing | 1420 | — |
| WildBench | 85.4% | — |
| EQ-Bench 4 | — | 1110 |
Frequently asked questions
Is GPT-4.1 better than Qwen3.7 Max?
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 35.9 on the Noometry Index.
Which is cheaper, GPT-4.1 or Qwen3.7 Max?
GPT-4.1 is cheaper. It lists at $2 per million input tokens and $8 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.
Is GPT-4.1 or Qwen3.7 Max better for coding?
Qwen3.7 Max scores higher on coding benchmarks: 50.4 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 1M.
How many benchmarks do GPT-4.1 and Qwen3.7 Max share?
23 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and Qwen3.7 Max has 33.