Model comparison
GPT-3.5-turbo vs Qwen3-4B
Qwen3-4B is the stronger model overall, scoring 31.9 to 23.2 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. GPT-3.5-turbo scores higher in 0 categories and Qwen3-4B in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-4B leads 29.7 to 6.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 2.2% for GPT-3.5-turbo and 52.2% for Qwen3-4B.
- Qwen3-4B has downloadable open weights; the other is API-only.
Side by side
| GPT-3.5-turbo | Qwen3-4B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 23.2 | 31.9 |
| Released | 2023-03-01 | 2025-04-29 |
| Weights | Proprietary | Open |
| Context window | 16K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.50 | — |
| Output $ / M tokens | $1.50 | — |
| Results tracked | 44 | 6 |
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Category by category
Coding Not comparable
GPT-3.5-turbo: 23.9 (#331), Qwen3-4B: —
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| WeirdML | 3.5% | — |
| BigCodeBench Instruct | 39.1% | — |
| LMArena Coding | 1136 | — |
| BigCodeBench Complete | 50.6% | — |
| HumanEval+ | 70.7% | — |
| MBPP+ | 69.7% | — |
Agentic & Tool Use Not comparable
GPT-3.5-turbo: —, Qwen3-4B: 27.6 (#100)
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 35.7% |
| METR Time Horizons | 21.5% | — |
Reasoning Qwen3-4B leads
GPT-3.5-turbo: 13.8 (#332), Qwen3-4B: 19.2 (#268)
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| Chess Puzzles | 0% | 4% |
| LMArena Hard Prompts | 1108 | — |
| Mystery Game Puzzles | 3% | — |
| DTBench | 48.5% | — |
| LMCA | 9.7% | — |
| Adversarial NLI | 58.1% | — |
| BIG-Bench Hard | 61.6% | — |
| CommonsenseQA 2.0 | 57% | — |
| Epoch Capabilities Index | 118.55 | — |
| ForecastBench | 50.4 | — |
| WinoGrande | 81.6% | — |
Math Qwen3-4B leads
GPT-3.5-turbo: 6.3 (#327), Qwen3-4B: 29.7 (#240)
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 2.2% | 52.2% |
| FrontierMath (Tiers 1-3) | 0% | — |
| MathArena Final-Answer Competitions | — | 38.5% |
| LMArena Math | 1142 | — |
| MATH Level 5 | 15.9% | — |
| GSM8K | 57.8% | — |
Knowledge Qwen3-4B leads
GPT-3.5-turbo: 10.0 (#303), Qwen3-4B: 33.0 (#208)
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| GPQA Diamond | 28% | 52.3% |
| Vectara Hallucination Rate | — | 5.7% |
| LMArena Expert | 1070 | — |
| ARC (AI2) Challenge | 87.4% | — |
| BoolQ | 87% | — |
| MMLU | 71.4% | — |
| OpenBookQA | 86% | — |
| TriviaQA | 85.8% | — |
Multilingual Not comparable
GPT-3.5-turbo: 31.5 (#258), Qwen3-4B: —
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| LMArena Non-English | 1108 | — |
| LMArena Chinese | 1075 | — |
| LMArena French | 1118 | — |
| LMArena German | 1090 | — |
| LMArena Japanese | 1043 | — |
| LMArena Korean | 1019 | — |
| LMArena Russian | 1123 | — |
| LMArena Spanish | 1121 | — |
Instruction Following Not comparable
GPT-3.5-turbo: 57.9 (#262), Qwen3-4B: —
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| LMArena Instruction Following | 1119 | — |
Long Context Not comparable
GPT-3.5-turbo: 34.0 (#254), Qwen3-4B: —
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| LMArena Longer Query | 1121 | — |
Writing & Preference Not comparable
GPT-3.5-turbo: 25.3 (#305), Qwen3-4B: —
| Benchmark | GPT-3.5-turbo | Qwen3-4B |
|---|---|---|
| LMArena Text | 1125 | — |
| LMArena Creative Writing | 1092 | — |
| EQ-Bench Creative Writing | 451 | — |
| LMArena Multi-Turn | 1117 | — |
Frequently asked questions
Is GPT-3.5-turbo better than Qwen3-4B?
Qwen3-4B is the stronger model overall, scoring 31.9 to 23.2 on the Noometry Index.
How many benchmarks do GPT-3.5-turbo and Qwen3-4B share?
3 benchmarks have published results for both models. GPT-3.5-turbo has 44 scored results on Noometry and Qwen3-4B has 6.