Model comparison
GPT-5.4 mini vs Qwen2.5-Max
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 40.7 on the Noometry Index.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GPT-5.4 mini scores higher in 8 categories and Qwen2.5-Max in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.4 mini leads 51.5 to 35.3.
Side by side
| GPT-5.4 mini | Qwen2.5-Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.0 | 40.7 |
| Released | 2026-03-17 | 2025-01-25 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.75 | — |
| Output $ / M tokens | $4.50 | — |
| Results tracked | 46 | 27 |
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Category by category
Coding GPT-5.4 mini leads
GPT-5.4 mini: 45.2 (#72), Qwen2.5-Max: 41.8 (#117)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Coding | 1438 | 1359 |
| FrontierCode | 27% | — |
| LMArena WebDev | 1397 | — |
| SciCode | 49.9% | — |
| WeirdML | 60.3% | — |
| LiveBench Coding | — | 64.4% |
| ALE-Bench | 1,189 | — |
Agentic & Tool Use Not comparable
GPT-5.4 mini: 29.9 (#81), Qwen2.5-Max: —
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| DeepResearch Bench | 36.3% | — |
Reasoning GPT-5.4 mini leads
GPT-5.4 mini: 30.4 (#85), Qwen2.5-Max: 25.6 (#147)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Hard Prompts | 1424 | 1360 |
| Epoch Capabilities Index | 148.84 | 132.53 |
| ARC-AGI-2 | 18.9% | — |
| Kagi LLM Benchmark | 37.9% | — |
| NYT Connections (extended) | 61.8% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 10% | — |
| Chess Puzzles | 24% | — |
| Thematic Generalization | 61.7% | — |
| LiveBench Reasoning | — | 51.4% |
| Mystery Game Puzzles | 11% | — |
| DTBench | 80% | — |
| LiveBench Data Analysis | — | 67.9% |
| LMCA | 40.8% | — |
| ForecastBench | 57 | — |
| LiveBench | — | 62.3% |
Math GPT-5.4 mini leads
GPT-5.4 mini: 45.5 (#75), Qwen2.5-Max: 36.9 (#162)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Math | 1419 | 1369 |
| FrontierMath (Tiers 1-3) | 51.2% | — |
| FrontierMath Tier 4 | 9.8% | — |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | 21% | — |
| LiveBench Math | — | 58.4% |
| FrontierMath (Feb 2025 set) | 28.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GPT-5.4 mini leads
GPT-5.4 mini: 51.5 (#67), Qwen2.5-Max: 35.3 (#186)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Expert | 1435 | 1337 |
| GPQA Diamond | 86.9% | — |
| SimpleQA Verified | 29.4% | — |
| Confabulations | — | 21.8% |
| Vectara Hallucination Rate | 5.5% | — |
Multimodal Not comparable
GPT-5.4 mini: 39.7 (#56), Qwen2.5-Max: —
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Vision | 1245 | — |
Multilingual GPT-5.4 mini leads
GPT-5.4 mini: 51.9 (#96), Qwen2.5-Max: 48.1 (#146)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Non-English | 1405 | 1352 |
| LMArena Chinese | 1446 | 1382 |
| LMArena French | 1440 | 1396 |
| LMArena German | 1409 | 1350 |
| LMArena Japanese | 1374 | 1300 |
| LMArena Korean | 1368 | 1304 |
| LMArena Russian | 1417 | 1353 |
| LMArena Spanish | 1405 | 1377 |
Instruction Following GPT-5.4 mini leads
GPT-5.4 mini: 74.1 (#102), Qwen2.5-Max: 71.3 (#152)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Instruction Following | 1405 | 1335 |
| LiveBench Instruction Following | — | 75.3% |
Long Context GPT-5.4 mini leads
GPT-5.4 mini: 43.0 (#112), Qwen2.5-Max: 41.4 (#142)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Longer Query | 1407 | 1358 |
Writing & Preference GPT-5.4 mini leads
GPT-5.4 mini: 64.0 (#58), Qwen2.5-Max: 55.4 (#146)
| Benchmark | GPT-5.4 mini | Qwen2.5-Max |
|---|---|---|
| LMArena Text | 1412 | 1367 |
| LMArena Creative Writing | 1370 | 1339 |
| LMArena Multi-Turn | 1429 | 1364 |
| Short-Story Creative Writing | — | 72.9% |
| EQ-Bench Creative Writing | 1665 | — |
| LiveBench Language | — | 56.3% |
Frequently asked questions
Is GPT-5.4 mini better than Qwen2.5-Max?
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 40.7 on the Noometry Index.
Is GPT-5.4 mini or Qwen2.5-Max better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 41.8 in the Noometry coding category.
How many benchmarks do GPT-5.4 mini and Qwen2.5-Max share?
18 benchmarks have published results for both models. GPT-5.4 mini has 46 scored results on Noometry and Qwen2.5-Max has 27.