Model comparison
GPT-4o mini vs Qwen1.5-14B
Qwen1.5-14B is the stronger model overall, scoring 32.1 to 25.4 on the Noometry Index.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. GPT-4o mini scores higher in 4 categories and Qwen1.5-14B in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen1.5-14B leads 29.9 to 9.9.
- Qwen1.5-14B has downloadable open weights; the other is API-only.
Side by side
| GPT-4o mini | Qwen1.5-14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 25.4 | 32.1 |
| Released | 2024-07-18 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 128K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.60 | — |
| Results tracked | 60 | 17 |
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Category by category
Coding Qwen1.5-14B leads
GPT-4o mini: 21.6 (#330), Qwen1.5-14B: 32.5 (#259)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1290 | 1138 |
| Aider Polyglot | 3.6% | — |
| WeirdML | 11.8% | — |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Not comparable
GPT-4o mini: 27.2 (#95), Qwen1.5-14B: —
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| BALROG | 17.4% | — |
Reasoning Qwen1.5-14B leads
GPT-4o mini: 8.7 (#343), Qwen1.5-14B: 20.5 (#217)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1267 | 1113 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 32.8% | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 54.4% | — |
| LiveBench Data Analysis | 50% | — |
| LMCA | 10.4% | — |
| Epoch Capabilities Index | 126.56 | — |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math Qwen1.5-14B leads
GPT-4o mini: 9.9 (#307), Qwen1.5-14B: 29.9 (#214)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1267 | 1125 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.9% | — |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge Qwen1.5-14B leads
GPT-4o mini: 17.7 (#279), Qwen1.5-14B: 29.3 (#230)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1235 | 1094 |
| MMLU | 81.8% | 68.6% |
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
Multimodal Not comparable
GPT-4o mini: 25.3 (#117), Qwen1.5-14B: —
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual GPT-4o mini leads
GPT-4o mini: 42.2 (#194), Qwen1.5-14B: 30.8 (#257)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1266 | 1095 |
| LMArena Chinese | 1264 | 1147 |
| LMArena French | 1296 | 1115 |
| LMArena German | 1272 | 1043 |
| LMArena Japanese | 1216 | 1019 |
| LMArena Russian | 1275 | 1046 |
| LMArena Spanish | 1276 | 1085 |
| LMArena Korean | 1195 | — |
Instruction Following GPT-4o mini leads
GPT-4o mini: 62.1 (#234), Qwen1.5-14B: 57.1 (#266)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1259 | 1102 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context GPT-4o mini leads
GPT-4o mini: 39.1 (#181), Qwen1.5-14B: 33.7 (#252)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1289 | 1113 |
Writing & Preference GPT-4o mini leads
GPT-4o mini: 39.7 (#243), Qwen1.5-14B: 33.7 (#270)
| Benchmark | GPT-4o mini | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1286 | 1128 |
| LMArena Creative Writing | 1268 | 1091 |
| LMArena Multi-Turn | 1285 | 1110 |
| Short-Story Creative Writing | 67.2% | — |
| EQ-Bench Creative Writing | 873 | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than Qwen1.5-14B?
Qwen1.5-14B is the stronger model overall, scoring 32.1 to 25.4 on the Noometry Index.
Is GPT-4o mini or Qwen1.5-14B better for coding?
Qwen1.5-14B scores higher on coding benchmarks: 32.5 versus 21.6 in the Noometry coding category.
How many benchmarks do GPT-4o mini and Qwen1.5-14B share?
17 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Qwen1.5-14B has 17.