# GPT-5 vs Qwen3.7 Max

> GPT-5 and Qwen3.7 Max score almost the same on the Noometry Index (50.9 vs 51.4), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/gpt-5-vs-qwen3-7-max
- Last updated: 2026-10-10
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. GPT-5 scores higher in 3 categories and Qwen3.7 Max in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where GPT-5 leads 69.5 to 45.4.
- The biggest single-benchmark swing is Chess Puzzles: 37% for GPT-5 and 19% for Qwen3.7 Max.
- GPT-5 is cheaper at $1.25 / $10 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Qwen3.7 Max accepts more context: 1M tokens versus 400K.

## Snapshot

| | GPT-5 | Qwen3.7 Max |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 50.9 | 51.4 |
| Rank | 37 | 35 |
| Context | 400K | 1M |
| Input $/M | $1.25 | $2.50 |
| Output $/M | $10 | $7.50 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-5: 50.7 (#39)
- Qwen3.7 Max: 50.2 (#43)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| SWE-bench Verified | 73.6% | 77.3% |
| LMArena WebDev | 1417 | 1515 |
| SciCode | 42.9% | 48.8% |
| LMArena Coding | 1436 | 1498 |
| ALE-Bench | 1,162 | 1,189 |
| SWE-bench Verified (bash only) | 65% | — |
| Aider Polyglot | 88% | — |
| GSO | 6.9% | — |
| WeirdML | 60.7% | — |
| AlgoTune | 1.67 | — |

## Agentic & Tool Use

- GPT-5: 33.0 (#53)
- Qwen3.7 Max: 21.8 (#129)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| Terminal-Bench | 49.6% | — |
| GDPval | 34.8% | — |
| Remote Labor Index | 1.7% | — |
| DeepResearch Bench | 49.6% | — |
| BALROG | 32.8% | — |
| GBAEval | — | 0.4% |
| LMArena Search | 1133 | — |
| METR Time Horizons | 69.6% | — |

## Reasoning

- GPT-5: 38.3 (#55)
- Qwen3.7 Max: 48.4 (#36)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| SimpleBench | 56.7% | 70.4% |
| CritPt | 12.6% | 13.4% |
| Chess Puzzles | 37% | 19% |
| EBR-Bench | 12.7% | 9.5% |
| LMArena Hard Prompts | 1415 | 1483 |
| Mystery Game Puzzles | 23% | 32% |
| DTBench | 90.7% | 92.3% |
| LMCA | 40% | 44% |
| Epoch Capabilities Index | 150 | 153.74 |
| ARC-AGI-2 | 9.9% | — |
| Kagi LLM Benchmark | 72.7% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 65.7% | — |
| EnigmaEval | 10.5% | — |
| ForecastBench | 61.4 | — |

## Math

- GPT-5: 54.6 (#36)
- Qwen3.7 Max: 62.3 (#26)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.4% | 64.6% |
| FrontierMath Tier 4 | 22% | 34.1% |
| OTIS Mock AIME 2024-2025 | 91.4% | 95.6% |
| ProofBench | 18% | 26% |
| LMArena Math | 1406 | 1488 |
| Omni-MATH | 64.7% | — |
| MATH Level 5 | 98.1% | — |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |

## Knowledge

- GPT-5: 56.5 (#37)
- Qwen3.7 Max: 61.7 (#24)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| GPQA Diamond | 86.2% | 90.9% |
| SimpleQA Verified | 50.1% | 55.8% |
| LMArena Expert | 1420 | 1488 |
| Humanity's Last Exam | 25.3% | — |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.3% | — |
| Vectara Hallucination Rate | 14.7% | — |
| GPQA (HELM) | 79.2% | — |

## Multimodal

- GPT-5: 46.1 (#12)
- Qwen3.7 Max: —

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| LMArena Vision | 1232 | — |
| GeoBench | 81% | — |
| VPCT | 66% | — |

## Multilingual

- GPT-5: 51.5 (#105)
- Qwen3.7 Max: 57.1 (#13)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1397 | 1475 |
| LMArena Chinese | 1423 | 1533 |
| LMArena Russian | 1406 | 1482 |
| LMArena French | 1409 | — |
| LMArena German | 1415 | — |
| LMArena Japanese | 1411 | — |
| LMArena Korean | 1361 | — |
| LMArena Spanish | 1398 | — |

## Instruction Following

- GPT-5: 74.0 (#107)
- Qwen3.7 Max: 76.9 (#34)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1388 | 1460 |
| IFEval | 87.5% | — |

## Long Context

- GPT-5: 69.5 (#2)
- Qwen3.7 Max: 45.4 (#34)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1399 | 1484 |
| Fiction.LiveBench | 97.2% | — |

## Writing & Preference

- GPT-5: 63.5 (#63)
- Qwen3.7 Max: 65.2 (#52)

| Benchmark | GPT-5 | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1406 | 1476 |
| LMArena Creative Writing | 1365 | 1450 |
| LMArena Multi-Turn | 1426 | 1482 |
| Short-Story Creative Writing | 86% | — |
| EQ-Bench Creative Writing | 1627 | — |
| WildBench | 85.7% | — |
| EQ-Bench 4 | — | 1110 |

## FAQ

### Is GPT-5 better than Qwen3.7 Max?

GPT-5 and Qwen3.7 Max score almost the same on the Noometry Index (50.9 vs 51.4), so choose on price, context window or the category you care about most.

### Which is cheaper, GPT-5 or Qwen3.7 Max?

GPT-5 is cheaper. It lists at $1.25 per million input tokens and $10 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.

### Is GPT-5 or Qwen3.7 Max better for coding?

They score almost the same on coding (50.7 vs 50.2); test both on your own repository before choosing.

### Which has the bigger context window?

Qwen3.7 Max does, with 1M tokens against 400K.

### How many benchmarks do GPT-5 and Qwen3.7 Max share?

30 benchmarks have published results for both models. GPT-5 has 69 scored results on Noometry and Qwen3.7 Max has 33.