Model comparison
GPT-4o mini vs QwQ-32B
QwQ-32B is the stronger model overall, scoring 39.8 to 25.5 on the Noometry Index.
Last verified . 34 shared benchmarks.
Summary
- They share 34 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and QwQ-32B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where QwQ-32B leads 38.0 to 10.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.9% for GPT-4o mini and 59.2% for QwQ-32B.
- QwQ-32B has downloadable open weights; the other is API-only.
Side by side
| GPT-4o mini | QwQ-32B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 25.5 | 39.8 |
| Released | 2024-07-18 | 2024-11-28 |
| Weights | Proprietary | Open |
| Context window | 128K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.60 | — |
| Results tracked | 60 | 36 |
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Category by category
Coding QwQ-32B leads
GPT-4o mini: 22.0 (#335), QwQ-32B: 35.4 (#226)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| Aider Polyglot | 3.6% | 20.9% |
| BigCodeBench Instruct | 46.1% | 44.6% |
| LiveBench Coding | 43.1% | 72.2% |
| LMArena Coding | 1290 | 1333 |
| BigCodeBench Complete | 57.4% | 54.4% |
| WeirdML | 11.8% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Not comparable
GPT-4o mini: 27.5 (#101), QwQ-32B: —
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| BALROG | 17.4% | — |
Reasoning QwQ-32B leads
GPT-4o mini: 8.7 (#347), QwQ-32B: 23.7 (#174)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| Chess Puzzles | 0% | 5% |
| LiveBench Reasoning | 32.8% | 83.5% |
| LMArena Hard Prompts | 1267 | 1325 |
| LiveBench Data Analysis | 50% | 65% |
| Epoch Capabilities Index | 126.56 | 137.6 |
| LiveBench | 41.3% | 72% |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 54.4% | — |
| LMCA | 10.4% | — |
| ForecastBench | — | 58.3 |
| PIQA | 88.7% | — |
Math QwQ-32B leads
GPT-4o mini: 10.4 (#314), QwQ-32B: 38.0 (#143)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.9% | 59.2% |
| LiveBench Math | 36.3% | 77.8% |
| LMArena Math | 1267 | 1359 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| Omni-MATH | 28% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge QwQ-32B leads
GPT-4o mini: 17.7 (#284), QwQ-32B: 37.2 (#158)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| GPQA Diamond | 37.7% | 65.3% |
| Confabulations | 37.2% | 15.6% |
| LMArena Expert | 1235 | 1324 |
| SimpleQA Verified | 8.3% | — |
| MMLU-Pro | 60.3% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Not comparable
GPT-4o mini: 25.9 (#122), QwQ-32B: —
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual QwQ-32B leads
GPT-4o mini: 42.0 (#199), QwQ-32B: 44.8 (#176)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| LMArena Non-English | 1266 | 1305 |
| LMArena Chinese | 1265 | 1378 |
| LMArena French | 1297 | 1336 |
| LMArena German | 1272 | 1313 |
| LMArena Japanese | 1216 | 1262 |
| LMArena Korean | 1195 | 1279 |
| LMArena Russian | 1275 | 1297 |
| LMArena Spanish | 1276 | 1354 |
Instruction Following QwQ-32B leads
GPT-4o mini: 61.9 (#239), QwQ-32B: 72.6 (#137)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| LiveBench Instruction Following | 56.8% | 81.8% |
| LMArena Instruction Following | 1258 | 1297 |
| IFEval | 78.2% | — |
Long Context QwQ-32B leads
GPT-4o mini: 39.1 (#186), QwQ-32B: 49.0 (#11)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| LMArena Longer Query | 1289 | 1308 |
| Fiction.LiveBench | — | 83.3% |
Writing & Preference QwQ-32B leads
GPT-4o mini: 39.5 (#248), QwQ-32B: 50.6 (#180)
| Benchmark | GPT-4o mini | QwQ-32B |
|---|---|---|
| LMArena Text | 1286 | 1329 |
| LMArena Creative Writing | 1268 | 1288 |
| Short-Story Creative Writing | 67.2% | 80.2% |
| EQ-Bench Creative Writing | 873 | 1257 |
| LMArena Multi-Turn | 1285 | 1314 |
| LiveBench Language | 28.6% | 51.4% |
| WildBench | 79.1% | — |
Frequently asked questions
Is GPT-4o mini better than QwQ-32B?
QwQ-32B is the stronger model overall, scoring 39.8 to 25.5 on the Noometry Index.
Is GPT-4o mini or QwQ-32B better for coding?
QwQ-32B scores higher on coding benchmarks: 35.4 versus 22.0 in the Noometry coding category.
How many benchmarks do GPT-4o mini and QwQ-32B share?
34 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and QwQ-32B has 36.