# GPT-6.1 Sol vs QwQ-32B

> GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 39.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-6-1-sol-vs-qwq-32b
- Last updated: 2026-10-12
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. GPT-6.1 Sol scores higher in 7 categories and QwQ-32B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6.1 Sol leads 81.9 to 23.7.
- The biggest single-benchmark swing is Chess Puzzles: 61% for GPT-6.1 Sol and 5% for QwQ-32B.
- QwQ-32B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 65.6 | 39.8 |
| Rank | 6 | 159 |
| Context | 1.05M | — |
| Input $/M | $2 | — |
| Output $/M | $10 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-6.1 Sol: 63.2 (#8)
- QwQ-32B: 35.4 (#226)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| LMArena Coding | 1487 | 1333 |
| DeepSWE | 75.2% | — |
| FrontierCode | 50.2% | — |
| Aider Polyglot | — | 20.9% |
| LMArena WebDev | 1755 | — |
| SciCode | 55.8% | — |
| BigCodeBench Instruct | — | 44.6% |
| LiveBench Coding | — | 72.2% |
| BigCodeBench Complete | — | 54.4% |

## Agentic & Tool Use

- GPT-6.1 Sol: 39.6 (#26)
- QwQ-32B: —

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| APEX-Agents | 60% | — |
| GDP.pdf | 32% | — |

## Reasoning

- GPT-6.1 Sol: 81.9 (#2)
- QwQ-32B: 23.7 (#174)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| Chess Puzzles | 61% | 5% |
| LMArena Hard Prompts | 1466 | 1325 |
| Epoch Capabilities Index | 166.09 | 137.6 |
| ARC-AGI-2 | 94.2% | — |
| NYT Connections (extended) | 95.5% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| EBR-Bench | 54.3% | — |
| LiveBench Reasoning | — | 83.5% |
| Mystery Game Puzzles | 80% | — |
| LiveBench Data Analysis | — | 65% |
| ForecastBench | — | 58.3 |
| LiveBench | — | 72% |

## Math

- GPT-6.1 Sol: 93.7 (#1)
- QwQ-32B: 38.0 (#143)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 59.2% |
| LMArena Math | 1464 | 1359 |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 100% | — |
| ProofBench | 99% | — |
| LiveBench Math | — | 77.8% |

## Knowledge

- GPT-6.1 Sol: 71.8 (#4)
- QwQ-32B: 37.2 (#158)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| GPQA Diamond | 95.4% | 65.3% |
| LMArena Expert | 1502 | 1324 |
| SimpleQA Verified | 73.9% | — |
| Confabulations | — | 15.6% |

## Multimodal

- GPT-6.1 Sol: 52.7 (#5)
- QwQ-32B: —

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| LMArena Vision | 1288 | — |
| Furniture Assembly | 80% | — |

## Multilingual

- GPT-6.1 Sol: 54.3 (#46)
- QwQ-32B: 44.8 (#176)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| LMArena Non-English | 1438 | 1305 |
| LMArena Chinese | 1477 | 1378 |
| LMArena Russian | 1455 | 1297 |
| LMArena French | — | 1336 |
| LMArena German | — | 1313 |
| LMArena Japanese | — | 1262 |
| LMArena Korean | — | 1279 |
| LMArena Spanish | — | 1354 |

## Instruction Following

- GPT-6.1 Sol: 77.0 (#29)
- QwQ-32B: 72.6 (#137)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| LMArena Instruction Following | 1468 | 1297 |
| LiveBench Instruction Following | — | 81.8% |

## Long Context

- GPT-6.1 Sol: 44.9 (#54)
- QwQ-32B: 49.0 (#11)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| LMArena Longer Query | 1465 | 1308 |
| Fiction.LiveBench | — | 83.3% |

## Writing & Preference

- GPT-6.1 Sol: 63.6 (#63)
- QwQ-32B: 50.6 (#180)

| Benchmark | GPT-6.1 Sol | QwQ-32B |
|---|---|---|
| LMArena Text | 1447 | 1329 |
| LMArena Creative Writing | 1432 | 1288 |
| LMArena Multi-Turn | 1449 | 1314 |
| Short-Story Creative Writing | — | 80.2% |
| EQ-Bench Creative Writing | — | 1257 |
| LiveBench Language | — | 51.4% |

## FAQ

### Is GPT-6.1 Sol better than QwQ-32B?

GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 39.8 on the Noometry Index.

### Is GPT-6.1 Sol or QwQ-32B better for coding?

GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 35.4 in the Noometry coding category.

### How many benchmarks do GPT-6.1 Sol and QwQ-32B share?

16 benchmarks have published results for both models. GPT-6.1 Sol has 34 scored results on Noometry and QwQ-32B has 36.