Model comparison
GPT-5.4 mini vs Qwen3 Max
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 43.7 on the Noometry Index.
Last verified . 29 shared benchmarks.
Summary
- They share 29 benchmarks with published results for both. GPT-5.4 mini scores higher in 6 categories and Qwen3 Max in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.4 mini leads 30.4 to 22.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 37.9% for GPT-5.4 mini and 72.5% for Qwen3 Max.
- GPT-5.4 mini is cheaper at $0.75 / $4.50 per million input/output tokens, against $1.20 / $6 for Qwen3 Max.
- GPT-5.4 mini accepts more context: 400K tokens versus 262K.
Side by side
| GPT-5.4 mini | Qwen3 Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.0 | 43.7 |
| Released | 2026-03-17 | 2025-09-23 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.75 | $1.20 |
| Output $ / M tokens | $4.50 | $6 |
| Results tracked | 46 | 33 |
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Category by category
Coding GPT-5.4 mini leads
GPT-5.4 mini: 45.2 (#72), Qwen3 Max: 43.0 (#93)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| LMArena Coding | 1438 | 1456 |
| ALE-Bench | 1,189 | 370.45 |
| FrontierCode | 27% | — |
| LMArena WebDev | 1397 | — |
| SciCode | 49.9% | — |
| WeirdML | 60.3% | — |
Agentic & Tool Use Not comparable
GPT-5.4 mini: 29.9 (#81), Qwen3 Max: —
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| DeepResearch Bench | 36.3% | — |
| Vending-Bench 2 | — | 71.56 |
Reasoning GPT-5.4 mini leads
GPT-5.4 mini: 30.4 (#85), Qwen3 Max: 22.6 (#190)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| Kagi LLM Benchmark | 37.9% | 72.5% |
| NYT Connections (extended) | 61.8% | 30.1% |
| Chess Puzzles | 24% | 4% |
| LMArena Hard Prompts | 1424 | 1448 |
| Mystery Game Puzzles | 11% | 5% |
| DTBench | 80% | 82.1% |
| LMCA | 40.8% | 28.3% |
| Epoch Capabilities Index | 148.84 | 142.38 |
| ARC-AGI-2 | 18.9% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 10% | — |
| Thematic Generalization | 61.7% | — |
| ForecastBench | 57 | — |
Math GPT-5.4 mini leads
GPT-5.4 mini: 45.5 (#75), Qwen3 Max: 38.7 (#131)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 51.2% | 18.9% |
| OTIS Mock AIME 2024-2025 | 88.9% | 73.3% |
| LMArena Math | 1419 | 1446 |
| FrontierMath Tier 4 | 9.8% | — |
| ProofBench | 21% | — |
| MATH Level 5 | — | 97.1% |
| 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), Qwen3 Max: 48.1 (#78)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| GPQA Diamond | 86.9% | 72.6% |
| SimpleQA Verified | 29.4% | 48.7% |
| LMArena Expert | 1435 | 1455 |
| Vectara Hallucination Rate | 5.5% | — |
Multimodal Not comparable
GPT-5.4 mini: 39.7 (#56), Qwen3 Max: —
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| LMArena Vision | 1245 | — |
Multilingual Qwen3 Max leads
GPT-5.4 mini: 51.9 (#96), Qwen3 Max: 53.7 (#62)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| LMArena Non-English | 1405 | 1429 |
| LMArena Chinese | 1446 | 1478 |
| LMArena French | 1440 | 1449 |
| LMArena German | 1409 | 1463 |
| LMArena Japanese | 1374 | 1397 |
| LMArena Korean | 1368 | 1399 |
| LMArena Russian | 1417 | 1428 |
| LMArena Spanish | 1405 | 1462 |
Instruction Following Too close to call
GPT-5.4 mini: 74.1 (#102), Qwen3 Max: 74.8 (#87)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| LMArena Instruction Following | 1405 | 1419 |
Long Context GPT-5.4 mini leads
GPT-5.4 mini: 43.0 (#112), Qwen3 Max: 41.6 (#134)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| LMArena Longer Query | 1407 | 1438 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 14.5% |
Writing & Preference GPT-5.4 mini leads
GPT-5.4 mini: 64.0 (#58), Qwen3 Max: 62.4 (#76)
| Benchmark | GPT-5.4 mini | Qwen3 Max |
|---|---|---|
| LMArena Text | 1412 | 1439 |
| LMArena Creative Writing | 1370 | 1402 |
| LMArena Multi-Turn | 1429 | 1446 |
| EQ-Bench Creative Writing | 1665 | — |
Frequently asked questions
Is GPT-5.4 mini better than Qwen3 Max?
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 43.7 on the Noometry Index.
Which is cheaper, GPT-5.4 mini or Qwen3 Max?
GPT-5.4 mini is cheaper. It lists at $0.75 per million input tokens and $4.50 per million output tokens; Qwen3 Max lists at $1.20 and $6.
Is GPT-5.4 mini or Qwen3 Max better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 43.0 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 262K.
How many benchmarks do GPT-5.4 mini and Qwen3 Max share?
29 benchmarks have published results for both models. GPT-5.4 mini has 46 scored results on Noometry and Qwen3 Max has 33.