Model comparison
o4-mini vs Qwen Max
o4-mini is the stronger model overall, scoring 41.6 to 34.7 on the Noometry Index.
Last verified . 23 shared benchmarks.
Alibaba (Qwen)Summary
- They share 23 benchmarks with published results for both. o4-mini scores higher in 7 categories and Qwen Max in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where o4-mini leads 40.8 to 22.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 81.7% for o4-mini and 16.1% for Qwen Max.
- o4-mini is cheaper at $1.10 / $4.40 per million input/output tokens, against $1.60 / $6.40 for Qwen Max.
- o4-mini accepts more context: 200K tokens versus 33K.
Side by side
| o4-mini | Qwen Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 41.6 | 34.7 |
| Released | 2025-04-16 | 2024-04-03 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 33K |
| Max output | 100K | 8K |
| Input $ / M tokens | $1.10 | $1.60 |
| Output $ / M tokens | $4.40 | $6.40 |
| Results tracked | 60 | 23 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding o4-mini leads
o4-mini: 40.9 (#127), Qwen Max: 30.7 (#292)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| Aider Polyglot | 72% | 21.8% |
| LMArena Coding | 1368 | 1288 |
| SWE-bench Verified (bash only) | 45% | — |
| GSO | 3.6% | — |
| WeirdML | 52.6% | — |
| CadEval | 62% | — |
| ALE-Bench | 826.17 | — |
| AlgoTune | 1.72 | — |
Agentic & Tool Use Not comparable
o4-mini: 32.6 (#61), Qwen Max: —
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| Berkeley Function Calling Leaderboard | 53.2% | — |
| GDPval | 25.3% | — |
| METR Time Horizons | 63.9% | — |
Reasoning Too close to call
o4-mini: 24.6 (#162), Qwen Max: 25.1 (#151)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| LMArena Hard Prompts | 1351 | 1269 |
| ARC-AGI-2 | 6.1% | — |
| SimpleBench | 38.7% | — |
| Kagi LLM Benchmark | 67.6% | — |
| ARC-AGI-1 | 58.7% | — |
| CritPt | 0.6% | — |
| Chess Puzzles | 26% | — |
| EnigmaEval | 9.2% | — |
| Mystery Game Puzzles | 5% | — |
| DTBench | 77.6% | — |
| LMCA | 26.5% | — |
| Epoch Capabilities Index | 145.64 | — |
| ForecastBench | 61.8 | — |
Math o4-mini leads
o4-mini: 40.8 (#89), Qwen Max: 22.3 (#276)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 81.7% | 16.1% |
| LMArena Math | 1389 | 1275 |
| MATH Level 5 | 97.8% | 67.2% |
| FrontierMath (Feb 2025 set) | 24.8% | 1% |
| FrontierMath (Tiers 1-3) | 36.1% | — |
| FrontierMath Tier 4 | 4.9% | — |
| Omni-MATH | 72% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge o4-mini leads
o4-mini: 43.6 (#91), Qwen Max: 30.3 (#228)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| GPQA Diamond | 79.6% | 56.1% |
| LMArena Expert | 1343 | 1248 |
| Humanity's Last Exam | 18.1% | — |
| SimpleQA Verified | 19.6% | — |
| MMLU-Pro | 82% | — |
| Confabulations | 15.8% | — |
| Vectara Hallucination Rate | 18.6% | — |
| GPQA (HELM) | 73.5% | — |
Multimodal Not comparable
o4-mini: 40.2 (#49), Qwen Max: —
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| LMArena Vision | 1194 | — |
| GeoBench | 64% | — |
| VPCT | 57.5% | — |
Multilingual o4-mini leads
o4-mini: 47.0 (#154), Qwen Max: 41.8 (#202)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| LMArena Non-English | 1337 | 1263 |
| LMArena Chinese | 1354 | 1254 |
| LMArena French | 1364 | 1330 |
| LMArena German | 1336 | 1254 |
| LMArena Japanese | 1308 | 1205 |
| LMArena Korean | 1312 | 1142 |
| LMArena Russian | 1334 | 1274 |
| LMArena Spanish | 1347 | 1290 |
Instruction Following o4-mini leads
o4-mini: 75.2 (#68), Qwen Max: 66.5 (#208)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| LMArena Instruction Following | 1321 | 1262 |
| IFEval | 92.8% | — |
Long Context o4-mini leads
o4-mini: 45.5 (#33), Qwen Max: 39.4 (#180)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| Fiction.LiveBench | 77.8% | 66.7% |
| LMArena Longer Query | 1315 | 1288 |
Writing & Preference o4-mini leads
o4-mini: 54.0 (#152), Qwen Max: 47.8 (#205)
| Benchmark | o4-mini | Qwen Max |
|---|---|---|
| LMArena Text | 1353 | 1282 |
| LMArena Creative Writing | 1294 | 1248 |
| LMArena Multi-Turn | 1350 | 1277 |
| Short-Story Creative Writing | 75% | — |
| WildBench | 85.4% | — |
Frequently asked questions
Is o4-mini better than Qwen Max?
o4-mini is the stronger model overall, scoring 41.6 to 34.7 on the Noometry Index.
Which is cheaper, o4-mini or Qwen Max?
o4-mini is cheaper. It lists at $1.10 per million input tokens and $4.40 per million output tokens; Qwen Max lists at $1.60 and $6.40.
Is o4-mini or Qwen Max better for coding?
o4-mini scores higher on coding benchmarks: 40.9 versus 30.7 in the Noometry coding category.
Which has the bigger context window?
o4-mini does, with 200K tokens against 33K.
How many benchmarks do o4-mini and Qwen Max share?
23 benchmarks have published results for both models. o4-mini has 60 scored results on Noometry and Qwen Max has 23.