Model comparison
GPT-4 Turbo vs Qwen3-1.7B
GPT-4 Turbo is the stronger model overall, scoring 30.5 to 26.6 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. GPT-4 Turbo scores higher in 1 category and Qwen3-1.7B in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-1.7B leads 16.3 to 9.0.
- The biggest single-benchmark swing is GPQA Diamond: 46.6% for GPT-4 Turbo and 38% for Qwen3-1.7B.
- Qwen3-1.7B has downloadable open weights; the other is API-only.
Side by side
| GPT-4 Turbo | Qwen3-1.7B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 30.5 | 26.6 |
| Released | 2023-11-06 | 2025-04-29 |
| Weights | Proprietary | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $10 | — |
| Output $ / M tokens | $30 | — |
| Results tracked | 36 | 4 |
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Category by category
Coding Not comparable
GPT-4 Turbo: 33.8 (#249), Qwen3-1.7B: —
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| WeirdML | 18% | — |
| BigCodeBench Instruct | 48.2% | — |
| LMArena Coding | 1268 | — |
| BigCodeBench Complete | 58.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73.3% | — |
Agentic & Tool Use Not comparable
GPT-4 Turbo: —, Qwen3-1.7B: 24.7 (#115)
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
| METR Time Horizons | 36.7% | — |
Reasoning Qwen3-1.7B leads
GPT-4 Turbo: 15.3 (#317), Qwen3-1.7B: 19.2 (#267)
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| Chess Puzzles | 6% | 0% |
| SimpleBench | 25.1% | — |
| LMArena Hard Prompts | 1251 | — |
| DTBench | 61.6% | — |
| LMCA | 9.8% | — |
| Epoch Capabilities Index | 127.25 | — |
| ForecastBench | 59.4 | — |
Math Qwen3-1.7B leads
GPT-4 Turbo: 9.0 (#322), Qwen3-1.7B: 16.3 (#294)
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.7% | 8.1% |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| LMArena Math | 1272 | — |
| MATH Level 5 | 46.7% | — |
Knowledge GPT-4 Turbo leads
GPT-4 Turbo: 24.3 (#268), Qwen3-1.7B: 19.6 (#278)
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 46.6% | 38% |
| Confabulations | 28.4% | — |
| LMArena Expert | 1223 | — |
| MMLU | 81.3% | — |
Multimodal Not comparable
GPT-4 Turbo: 30.6 (#110), Qwen3-1.7B: —
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| LMArena Vision | 1090 | — |
Multilingual Not comparable
GPT-4 Turbo: 40.5 (#216), Qwen3-1.7B: —
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1245 | — |
| LMArena Chinese | 1242 | — |
| LMArena French | 1276 | — |
| LMArena German | 1259 | — |
| LMArena Japanese | 1194 | — |
| LMArena Korean | 1187 | — |
| LMArena Russian | 1259 | — |
| LMArena Spanish | 1260 | — |
Instruction Following Not comparable
GPT-4 Turbo: 65.8 (#216), Qwen3-1.7B: —
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1249 | — |
Long Context Not comparable
GPT-4 Turbo: 38.0 (#206), Qwen3-1.7B: —
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1254 | — |
Writing & Preference Not comparable
GPT-4 Turbo: 47.7 (#206), Qwen3-1.7B: —
| Benchmark | GPT-4 Turbo | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1272 | — |
| LMArena Creative Writing | 1269 | — |
| LMArena Multi-Turn | 1267 | — |
Frequently asked questions
Is GPT-4 Turbo better than Qwen3-1.7B?
GPT-4 Turbo is the stronger model overall, scoring 30.5 to 26.6 on the Noometry Index.
How many benchmarks do GPT-4 Turbo and Qwen3-1.7B share?
3 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Qwen3-1.7B has 4.