# GPT-4.1 vs QwQ-32B

> QwQ-32B is the stronger model overall, scoring 39.4 to 35.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4-1-vs-qwq-32b
- Last updated: 2026-10-10
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. GPT-4.1 scores higher in 2 categories and QwQ-32B in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where QwQ-32B leads 36.2 to 21.4.
- The biggest single-benchmark swing is Aider Polyglot: 52.4% for GPT-4.1 and 20.9% for QwQ-32B.
- QwQ-32B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4.1 | QwQ-32B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 35.7 | 39.4 |
| Rank | 215 | 153 |
| Context | 1.05M | — |
| Input $/M | $2 | — |
| Output $/M | $8 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-4.1: 34.2 (#228)
- QwQ-32B: 34.9 (#220)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| Aider Polyglot | 52.4% | 20.9% |
| LMArena Coding | 1391 | 1333 |
| SWE-bench Verified | 48.5% | — |
| SWE-bench Verified (bash only) | 39.6% | — |
| WeirdML | 39% | — |
| BigCodeBench Instruct | — | 44.6% |
| LiveBench Coding | — | 72.2% |
| BigCodeBench Complete | — | 54.4% |
| CadEval | 42% | — |
| ALE-Bench | 558.1 | — |

## Agentic & Tool Use

- GPT-4.1: 34.4 (#40)
- QwQ-32B: —

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | — |

## Reasoning

- GPT-4.1: 11.7 (#334)
- QwQ-32B: 22.9 (#171)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| Chess Puzzles | 6% | 5% |
| LMArena Hard Prompts | 1384 | 1326 |
| Epoch Capabilities Index | 136.79 | 137.6 |
| ForecastBench | 61.5 | 58.3 |
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| Kagi LLM Benchmark | 52.3% | — |
| ARC-AGI-1 | 5.5% | — |
| EnigmaEval | 2.2% | — |
| LiveBench Reasoning | — | 83.5% |
| DTBench | 68.3% | — |
| LiveBench Data Analysis | — | 65% |
| LMCA | 25.6% | — |
| LiveBench | — | 72% |

## Math

- GPT-4.1: 21.4 (#269)
- QwQ-32B: 36.2 (#123)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 38.3% | 59.2% |
| LMArena Math | 1369 | 1359 |
| FrontierMath (Tiers 1-3) | 6% | — |
| Omni-MATH | 47.1% | — |
| LiveBench Math | — | 77.8% |
| MATH Level 5 | 83% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- GPT-4.1: 37.0 (#152)
- QwQ-32B: 37.2 (#150)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| GPQA Diamond | 66.9% | 65.3% |
| LMArena Expert | 1364 | 1323 |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| MMLU-Pro | 81.1% | — |
| Confabulations | — | 15.6% |
| Vectara Hallucination Rate | 5.6% | — |
| GPQA (HELM) | 65.9% | — |

## Multimodal

- GPT-4.1: 37.5 (#66)
- QwQ-32B: —

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| LMArena Vision | 1210 | — |
| GeoBench | 72% | — |

## Multilingual

- GPT-4.1: 49.6 (#128)
- QwQ-32B: 45.0 (#171)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| LMArena Non-English | 1370 | 1306 |
| LMArena Chinese | 1382 | 1378 |
| LMArena French | 1383 | 1337 |
| LMArena German | 1380 | 1313 |
| LMArena Japanese | 1320 | 1263 |
| LMArena Korean | 1339 | 1278 |
| LMArena Russian | 1377 | 1297 |
| LMArena Spanish | 1375 | 1353 |

## Instruction Following

- GPT-4.1: 71.5 (#148)
- QwQ-32B: 72.8 (#131)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| LMArena Instruction Following | 1367 | 1297 |
| LiveBench Instruction Following | — | 81.8% |
| IFEval | 83.8% | — |

## Long Context

- GPT-4.1: 40.0 (#158)
- QwQ-32B: 49.0 (#11)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| Fiction.LiveBench | 63.9% | 83.3% |
| LMArena Longer Query | 1385 | 1308 |

## Writing & Preference

- GPT-4.1: 57.8 (#120)
- QwQ-32B: 50.9 (#175)

| Benchmark | GPT-4.1 | QwQ-32B |
|---|---|---|
| LMArena Text | 1383 | 1329 |
| LMArena Creative Writing | 1363 | 1288 |
| EQ-Bench Creative Writing | 1420 | 1257 |
| LMArena Multi-Turn | 1398 | 1314 |
| Short-Story Creative Writing | — | 80.2% |
| WildBench | 85.4% | — |
| LiveBench Language | — | 51.4% |

## FAQ

### Is GPT-4.1 better than QwQ-32B?

QwQ-32B is the stronger model overall, scoring 39.4 to 35.7 on the Noometry Index.

### Is GPT-4.1 or QwQ-32B better for coding?

They score almost the same on coding (34.2 vs 34.9); test both on your own repository before choosing.

### How many benchmarks do GPT-4.1 and QwQ-32B share?

25 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and QwQ-32B has 36.