Model comparison
GPT-5.4 mini vs Qwen3-Coder 480B-A35B Instruct
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 38.1 on the Noometry Index.
Last verified . 21 shared benchmarks.
Alibaba (Qwen)Summary
- They share 21 benchmarks with published results for both. GPT-5.4 mini scores higher in 9 categories and Qwen3-Coder 480B-A35B Instruct 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 37.0.
- The biggest single-benchmark swing is WeirdML: 60.3% for GPT-5.4 mini and 41.2% for Qwen3-Coder 480B-A35B Instruct.
- GPT-5.4 mini is cheaper at $0.75 / $4.50 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
- GPT-5.4 mini accepts more context: 400K tokens versus 262K.
- Qwen3-Coder 480B-A35B Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.0 | 38.1 |
| Released | 2026-03-17 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.75 | $1.50 |
| Output $ / M tokens | $4.50 | $7.50 |
| Results tracked | 46 | 25 |
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Category by category
Coding GPT-5.4 mini leads
GPT-5.4 mini: 45.2 (#72), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena WebDev | 1397 | 1275 |
| WeirdML | 60.3% | 41.2% |
| LMArena Coding | 1438 | 1412 |
| ALE-Bench | 1,189 | 461.45 |
| FrontierCode | 27% | — |
| SWE-bench Verified (bash only) | — | 55.4% |
| SciCode | 49.9% | — |
| GSO | — | 4.9% |
| AlgoTune | — | 1.44 |
Agentic & Tool Use GPT-5.4 mini leads
GPT-5.4 mini: 29.9 (#81), Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| DeepResearch Bench | 36.3% | — |
Reasoning GPT-5.4 mini leads
GPT-5.4 mini: 30.4 (#85), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 37.9% | 49.5% |
| LMArena Hard Prompts | 1424 | 1372 |
| ARC-AGI-2 | 18.9% | — |
| NYT Connections (extended) | 61.8% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 10% | — |
| Chess Puzzles | 24% | — |
| Thematic Generalization | 61.7% | — |
| Mystery Game Puzzles | 11% | — |
| DTBench | 80% | — |
| LMCA | 40.8% | — |
| Epoch Capabilities Index | 148.84 | — |
| ForecastBench | 57 | — |
Math GPT-5.4 mini leads
GPT-5.4 mini: 45.5 (#75), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1419 | 1365 |
| FrontierMath (Tiers 1-3) | 51.2% | — |
| FrontierMath Tier 4 | 9.8% | — |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | 21% | — |
| 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-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1435 | 1338 |
| GPQA Diamond | 86.9% | — |
| SimpleQA Verified | 29.4% | — |
| Vectara Hallucination Rate | 5.5% | — |
Multimodal Not comparable
GPT-5.4 mini: 39.7 (#56), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1245 | — |
Multilingual GPT-5.4 mini leads
GPT-5.4 mini: 51.9 (#96), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1405 | 1346 |
| LMArena Chinese | 1446 | 1357 |
| LMArena French | 1440 | 1398 |
| LMArena German | 1409 | 1325 |
| LMArena Japanese | 1374 | 1310 |
| LMArena Korean | 1368 | 1305 |
| LMArena Russian | 1417 | 1366 |
| LMArena Spanish | 1405 | 1360 |
Instruction Following GPT-5.4 mini leads
GPT-5.4 mini: 74.1 (#102), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1405 | 1355 |
Long Context Too close to call
GPT-5.4 mini: 43.0 (#112), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1407 | 1378 |
Writing & Preference GPT-5.4 mini leads
GPT-5.4 mini: 64.0 (#58), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | GPT-5.4 mini | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1412 | 1357 |
| LMArena Creative Writing | 1370 | 1333 |
| LMArena Multi-Turn | 1429 | 1365 |
| EQ-Bench Creative Writing | 1665 | — |
Frequently asked questions
Is GPT-5.4 mini better than Qwen3-Coder 480B-A35B Instruct?
GPT-5.4 mini is the stronger model overall, scoring 45.0 to 38.1 on the Noometry Index.
Which is cheaper, GPT-5.4 mini or Qwen3-Coder 480B-A35B Instruct?
GPT-5.4 mini is cheaper. It lists at $0.75 per million input tokens and $4.50 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is GPT-5.4 mini or Qwen3-Coder 480B-A35B Instruct better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 35.5 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-Coder 480B-A35B Instruct share?
21 benchmarks have published results for both models. GPT-5.4 mini has 46 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.