Model comparison
GPT-4 vs Qwen3-1.7B
GPT-4 is the stronger model overall, scoring 28.9 to 26.2 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. GPT-4 scores higher in 0 categories and Qwen3-1.7B in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-1.7B leads 15.4 to 10.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.1% for GPT-4 and 8.1% for Qwen3-1.7B.
- Qwen3-1.7B has downloadable open weights; the other is API-only.
Side by side
| GPT-4 | Qwen3-1.7B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 28.9 | 26.2 |
| Released | 2023-03-14 | 2025-04-29 |
| Weights | Proprietary | Open |
| Context window | 8K | — |
| Max output | 8K | — |
| Input $ / M tokens | $30 | — |
| Output $ / M tokens | $60 | — |
| Results tracked | 38 | 4 |
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Category by category
Coding Not comparable
GPT-4: 31.2 (#277), Qwen3-1.7B: —
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| WeirdML | 12.4% | — |
| BigCodeBench Instruct | 46% | — |
| LMArena Coding | 1254 | — |
| BigCodeBench Complete | 57.2% | — |
| HumanEval+ | 79.3% | — |
Agentic & Tool Use Not comparable
GPT-4: —, Qwen3-1.7B: 24.5 (#108)
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
| METR Time Horizons | 36.1% | — |
Reasoning Qwen3-1.7B leads
GPT-4: 17.3 (#285), Qwen3-1.7B: 18.5 (#263)
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| Chess Puzzles | 4% | 0% |
| LMArena Hard Prompts | 1241 | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 62.7% | — |
| LMCA | 17.1% | — |
| BIG-Bench Hard | 75.1% | — |
| Epoch Capabilities Index | 125.88 | — |
| ForecastBench | 57.8 | — |
| HellaSwag | 95.3% | — |
| WinoGrande | 87.5% | — |
Math Qwen3-1.7B leads
GPT-4: 10.1 (#304), Qwen3-1.7B: 15.4 (#288)
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.1% | 8.1% |
| LMArena Math | 1269 | — |
| MATH Level 5 | 23% | — |
| GSM8K | 92% | — |
Knowledge Qwen3-1.7B leads
GPT-4: 18.4 (#277), Qwen3-1.7B: 19.6 (#273)
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 35.7% | 38% |
| LMArena Expert | 1211 | — |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |
Multilingual Not comparable
GPT-4: 40.8 (#210), Qwen3-1.7B: —
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| 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 Not comparable
GPT-4: 65.5 (#217), Qwen3-1.7B: —
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1241 | — |
Long Context Not comparable
GPT-4: 37.7 (#207), Qwen3-1.7B: —
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1244 | — |
Writing & Preference Not comparable
GPT-4: 35.0 (#263), Qwen3-1.7B: —
| Benchmark | GPT-4 | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1263 | — |
| LMArena Creative Writing | 1244 | — |
| EQ-Bench Creative Writing | 752 | — |
| LMArena Multi-Turn | 1257 | — |
Frequently asked questions
Is GPT-4 better than Qwen3-1.7B?
GPT-4 is the stronger model overall, scoring 28.9 to 26.2 on the Noometry Index.
How many benchmarks do GPT-4 and Qwen3-1.7B share?
3 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen3-1.7B has 4.