# GPT-4 vs Qwen2.5 32B Instruct

> GPT-4 and Qwen2.5 32B Instruct score almost the same on the Noometry Index (28.9 vs 29.7), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/gpt-4-vs-qwen2-5-32b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 7

## Summary

- They share 7 benchmarks with published results for both. GPT-4 scores higher in 0 categories and Qwen2.5 32B Instruct in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in coding, where Qwen2.5 32B Instruct leads 38.1 to 31.2.
- The biggest single-benchmark swing is MATH Level 5: 23% for GPT-4 and 56.1% for Qwen2.5 32B Instruct.
- Qwen2.5 32B Instruct is cheaper at $0.70 / $2.80 per million input/output tokens, against $30 / $60 for GPT-4.
- Qwen2.5 32B Instruct accepts more context: 131K tokens versus 8K.
- Qwen2.5 32B Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 28.9 | 29.7 |
| Rank | 308 | 291 |
| Context | 8K | 131K |
| Input $/M | $30 | $0.70 |
| Output $/M | $60 | $2.80 |
| Weights | Proprietary | Open |

## Coding

- GPT-4: 31.2 (#277)
- Qwen2.5 32B Instruct: 38.1 (#165)

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| BigCodeBench Instruct | 46% | 45% |
| BigCodeBench Complete | 57.2% | 52.3% |
| WeirdML | 12.4% | — |
| LMArena Coding | 1254 | — |
| HumanEval+ | 79.3% | — |

## Agentic & Tool Use

- GPT-4: —
- Qwen2.5 32B Instruct: —

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| METR Time Horizons | 36.1% | — |

## Reasoning

- GPT-4: 17.3 (#285)
- Qwen2.5 32B Instruct: 18.5 (#262)

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| Chess Puzzles | 4% | 0% |
| Epoch Capabilities Index | 125.88 | 128.52 |
| LMArena Hard Prompts | 1241 | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 62.7% | — |
| LMCA | 17.1% | — |
| BIG-Bench Hard | 75.1% | — |
| ForecastBench | 57.8 | — |
| HellaSwag | 95.3% | — |
| WinoGrande | 87.5% | — |

## Math

- GPT-4: 10.1 (#304)
- Qwen2.5 32B Instruct: 15.3 (#289)

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.1% | 7.4% |
| MATH Level 5 | 23% | 56.1% |
| LMArena Math | 1269 | — |
| GSM8K | 92% | — |

## Knowledge

- GPT-4: 18.4 (#277)
- Qwen2.5 32B Instruct: 24.9 (#259)

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 35.7% | 46.1% |
| LMArena Expert | 1211 | — |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |

## Multilingual

- GPT-4: 40.8 (#210)
- Qwen2.5 32B Instruct: —

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1246 | — |
| LMArena Chinese | 1242 | — |
| LMArena French | 1282 | — |
| LMArena German | 1251 | — |
| LMArena Japanese | 1209 | — |
| LMArena Korean | 1184 | — |
| LMArena Russian | 1251 | — |
| LMArena Spanish | 1261 | — |

## Instruction Following

- GPT-4: 65.5 (#217)
- Qwen2.5 32B Instruct: —

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Instruction Following | 1241 | — |

## Long Context

- GPT-4: 37.7 (#207)
- Qwen2.5 32B Instruct: —

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Longer Query | 1244 | — |

## Writing & Preference

- GPT-4: 35.0 (#263)
- Qwen2.5 32B Instruct: —

| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1263 | — |
| LMArena Creative Writing | 1244 | — |
| EQ-Bench Creative Writing | 752 | — |
| LMArena Multi-Turn | 1257 | — |

## FAQ

### Is GPT-4 better than Qwen2.5 32B Instruct?

GPT-4 and Qwen2.5 32B Instruct score almost the same on the Noometry Index (28.9 vs 29.7), so choose on price, context window or the category you care about most.

### Which is cheaper, GPT-4 or Qwen2.5 32B Instruct?

Qwen2.5 32B Instruct is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; GPT-4 lists at $30 and $60.

### Is GPT-4 or Qwen2.5 32B Instruct better for coding?

Qwen2.5 32B Instruct scores higher on coding benchmarks: 38.1 versus 31.2 in the Noometry coding category.

### Which has the bigger context window?

Qwen2.5 32B Instruct does, with 131K tokens against 8K.

### How many benchmarks do GPT-4 and Qwen2.5 32B Instruct share?

7 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen2.5 32B Instruct has 7.