Model comparison
GPT-4 vs Qwen1.5-72B
Qwen1.5-72B is the stronger model overall, scoring 30.8 to 29.1 on the Noometry Index.
Last verified . 21 shared benchmarks.
Alibaba (Qwen)Summary
- They share 21 benchmarks with published results for both. GPT-4 scores higher in 4 categories and Qwen1.5-72B in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen1.5-72B leads 33.2 to 10.8.
- The biggest single-benchmark swing is BigCodeBench Complete: 57.2% for GPT-4 and 40.3% for Qwen1.5-72B.
- Qwen1.5-72B has downloadable open weights; the other is API-only.
Side by side
| GPT-4 | Qwen1.5-72B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 29.1 | 30.8 |
| Released | 2023-03-14 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 8K | — |
| Max output | 8K | — |
| Input $ / M tokens | $30 | — |
| Output $ / M tokens | $60 | — |
| Results tracked | 38 | 22 |
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Category by category
Coding Too close to call
GPT-4: 31.6 (#283), Qwen1.5-72B: 31.9 (#277)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| BigCodeBench Instruct | 46% | 33.2% |
| LMArena Coding | 1254 | 1165 |
| BigCodeBench Complete | 57.2% | 40.3% |
| HumanEval+ | 79.3% | 59.1% |
| WeirdML | 12.4% | — |
| MBPP+ | — | 61.6% |
Agentic & Tool Use Not comparable
GPT-4: —, Qwen1.5-72B: —
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| METR Time Horizons | 36.1% | — |
Reasoning Qwen1.5-72B leads
GPT-4: 17.8 (#289), Qwen1.5-72B: 22.2 (#203)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1148 |
| Chess Puzzles | 4% | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 62.7% | — |
| LMCA | 17.1% | — |
| BIG-Bench Hard | 75.1% | — |
| Epoch Capabilities Index | 125.89 | — |
| ForecastBench | 57.8 | — |
| HellaSwag | 95.3% | — |
| WinoGrande | 87.5% | — |
Math Qwen1.5-72B leads
GPT-4: 10.8 (#309), Qwen1.5-72B: 33.2 (#205)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| LMArena Math | 1269 | 1164 |
| OTIS Mock AIME 2024-2025 | 1.1% | — |
| MATH Level 5 | 23% | — |
| GSM8K | 92% | — |
Knowledge GPT-4 leads
GPT-4: 18.4 (#282), Qwen1.5-72B: 11.5 (#300)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| GPQA Diamond | 35.7% | 28.8% |
| LMArena Expert | 1211 | 1136 |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |
Multilingual GPT-4 leads
GPT-4: 40.6 (#215), Qwen1.5-72B: 33.2 (#253)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| LMArena Non-English | 1246 | 1135 |
| LMArena Chinese | 1242 | 1186 |
| LMArena French | 1283 | 1159 |
| LMArena German | 1251 | 1084 |
| LMArena Japanese | 1209 | 1061 |
| LMArena Korean | 1184 | 1050 |
| LMArena Russian | 1251 | 1104 |
| LMArena Spanish | 1261 | 1110 |
Instruction Following GPT-4 leads
GPT-4: 65.3 (#222), Qwen1.5-72B: 59.3 (#256)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| LMArena Instruction Following | 1241 | 1141 |
Long Context GPT-4 leads
GPT-4: 37.7 (#212), Qwen1.5-72B: 35.1 (#243)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| LMArena Longer Query | 1244 | 1157 |
Writing & Preference Qwen1.5-72B leads
GPT-4: 34.9 (#268), Qwen1.5-72B: 37.3 (#258)
| Benchmark | GPT-4 | Qwen1.5-72B |
|---|---|---|
| LMArena Text | 1263 | 1166 |
| LMArena Creative Writing | 1244 | 1137 |
| LMArena Multi-Turn | 1257 | 1160 |
| EQ-Bench Creative Writing | 752 | — |
Frequently asked questions
Is GPT-4 better than Qwen1.5-72B?
Qwen1.5-72B is the stronger model overall, scoring 30.8 to 29.1 on the Noometry Index.
Is GPT-4 or Qwen1.5-72B better for coding?
They score almost the same on coding (31.6 vs 31.9); test both on your own repository before choosing.
How many benchmarks do GPT-4 and Qwen1.5-72B share?
21 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen1.5-72B has 22.