# GPT-6 Sol vs Qwen2.5-Coder-32B

> GPT-6 Sol is the stronger model overall, scoring 49.2 to 32.9 on the Noometry Index. Qwen2.5-Coder-32B costs 5.4× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-6-sol-vs-qwen2-5-coder-32b
- Last updated: 2026-10-10
- Shared benchmarks: 12

## Summary

- They share 12 benchmarks with published results for both. GPT-6 Sol scores higher in 8 categories and Qwen2.5-Coder-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-6 Sol leads 59.6 to 22.4.
- Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 33K.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 49.2 | 32.9 |
| Rank | 46 | 239 |
| Context | 1.05M | 33K |
| Input $/M | $2 | $0.66 |
| Output $/M | $10 | $1 |
| Weights | Proprietary | Open |

## Coding

- GPT-6 Sol: 59.6 (#11)
- Qwen2.5-Coder-32B: 22.4 (#328)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Coding | 1453 | 1276 |
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| LMArena WebDev | 1692 | — |
| BigCodeBench Instruct | — | 49% |
| LiveBench Coding | — | 56.9% |
| BigCodeBench Complete | — | 58% |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |

## Agentic & Tool Use

- GPT-6 Sol: 33.5 (#49)
- Qwen2.5-Coder-32B: —

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| GDP.pdf | 28% | — |

## Reasoning

- GPT-6 Sol: 49.3 (#34)
- Qwen2.5-Coder-32B: 20.4 (#220)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Hard Prompts | 1420 | 1251 |
| NYT Connections (extended) | 90.1% | — |
| EBR-Bench | 53.3% | — |
| LiveBench Reasoning | — | 42.1% |
| LiveBench Data Analysis | — | 49.9% |
| Epoch Capabilities Index | — | 119.41 |
| HellaSwag | — | 83% |
| LiveBench | — | 46.2% |
| WinoGrande | — | 80.8% |

## Math

- GPT-6 Sol: 35.8 (#135)
- Qwen2.5-Coder-32B: 30.8 (#203)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Math | 1404 | 1251 |
| LiveBench Math | — | 46.6% |
| GSM8K | — | 93% |

## Knowledge

- GPT-6 Sol: 43.0 (#87)
- Qwen2.5-Coder-32B: 32.9 (#200)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1449 | 1221 |
| Vectara Hallucination Rate | 6.5% | — |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |

## Multimodal

- GPT-6 Sol: 47.6 (#9)
- Qwen2.5-Coder-32B: —

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| Furniture Assembly | 58.3% | — |

## Multilingual

- GPT-6 Sol: 51.0 (#113)
- Qwen2.5-Coder-32B: 38.0 (#230)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1389 | 1205 |
| LMArena Chinese | 1416 | 1222 |
| LMArena Russian | 1407 | 1228 |
| LMArena Spanish | 1377 | — |

## Instruction Following

- GPT-6 Sol: 74.4 (#97)
- Qwen2.5-Coder-32B: 61.6 (#240)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Instruction Following | 1406 | 1223 |
| LiveBench Instruction Following | — | 58.7% |

## Long Context

- GPT-6 Sol: 43.2 (#100)
- Qwen2.5-Coder-32B: 37.9 (#204)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1415 | 1251 |

## Writing & Preference

- GPT-6 Sol: 72.3 (#15)
- Qwen2.5-Coder-32B: 41.8 (#235)

| Benchmark | GPT-6 Sol | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1396 | 1230 |
| LMArena Creative Writing | 1392 | 1174 |
| LMArena Multi-Turn | 1405 | 1222 |
| EQ-Bench Creative Writing | 2125 | — |
| LiveBench Language | — | 23.3% |

## FAQ

### Is GPT-6 Sol better than Qwen2.5-Coder-32B?

GPT-6 Sol is the stronger model overall, scoring 49.2 to 32.9 on the Noometry Index. Qwen2.5-Coder-32B costs 5.4× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

### Which is cheaper, GPT-6 Sol or Qwen2.5-Coder-32B?

Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; GPT-6 Sol lists at $2 and $10.

### Is GPT-6 Sol or Qwen2.5-Coder-32B better for coding?

GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 22.4 in the Noometry coding category.

### Which has the bigger context window?

GPT-6 Sol does, with 1.05M tokens against 33K.

### How many benchmarks do GPT-6 Sol and Qwen2.5-Coder-32B share?

12 benchmarks have published results for both models. GPT-6 Sol has 22 scored results on Noometry and Qwen2.5-Coder-32B has 31.