Model comparison
GPT-4 vs Qwen2.5 32B Instruct
GPT-4 and Qwen2.5 32B Instruct score almost the same on the Noometry Index (29.1 vs 30.1), so choose on price, context window or the category you care about most.
Last verified . 7 shared benchmarks.
Alibaba (Qwen)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 38.7 to 31.6.
- 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.
Side by side
| GPT-4 | Qwen2.5 32B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 29.1 | 30.1 |
| Released | 2023-03-14 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | 8K | 131K |
| Max output | 8K | 8K |
| Input $ / M tokens | $30 | $0.70 |
| Output $ / M tokens | $60 | $2.80 |
| Results tracked | 38 | 7 |
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Category by category
Coding Qwen2.5 32B Instruct leads
GPT-4: 31.6 (#283), Qwen2.5 32B Instruct: 38.7 (#169)
| 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 Not comparable
GPT-4: —, Qwen2.5 32B Instruct: —
| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| METR Time Horizons | 36.1% | — |
Reasoning Qwen2.5 32B Instruct leads
GPT-4: 17.8 (#289), Qwen2.5 32B Instruct: 19.2 (#266)
| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| Chess Puzzles | 4% | 0% |
| Epoch Capabilities Index | 125.89 | 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 Qwen2.5 32B Instruct leads
GPT-4: 10.8 (#309), Qwen2.5 32B Instruct: 16.2 (#296)
| 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 Qwen2.5 32B Instruct leads
GPT-4: 18.4 (#282), Qwen2.5 32B Instruct: 24.9 (#266)
| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 35.7% | 46.1% |
| LMArena Expert | 1211 | — |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |
Multilingual Not comparable
GPT-4: 40.6 (#215), Qwen2.5 32B Instruct: —
| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1246 | — |
| LMArena Chinese | 1242 | — |
| LMArena French | 1283 | — |
| LMArena German | 1251 | — |
| LMArena Japanese | 1209 | — |
| LMArena Korean | 1184 | — |
| LMArena Russian | 1251 | — |
| LMArena Spanish | 1261 | — |
Instruction Following Not comparable
GPT-4: 65.3 (#222), Qwen2.5 32B Instruct: —
| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Instruction Following | 1241 | — |
Long Context Not comparable
GPT-4: 37.7 (#212), Qwen2.5 32B Instruct: —
| Benchmark | GPT-4 | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Longer Query | 1244 | — |
Writing & Preference Not comparable
GPT-4: 34.9 (#268), 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 | — |
Frequently asked questions
Is GPT-4 better than Qwen2.5 32B Instruct?
GPT-4 and Qwen2.5 32B Instruct score almost the same on the Noometry Index (29.1 vs 30.1), 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: 38.7 versus 31.6 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.