Model comparison
GPT-5.4 Pro vs Qwen3-Coder 480B-A35B Instruct
GPT-5.4 Pro is the stronger model overall, scoring 58.8 to 37.7 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 23× less per token, which makes it the better buy when GPT-5.4 Pro's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Alibaba (Qwen)Summary
- They share 1 benchmark with published results for both. GPT-5.4 Pro scores higher in 4 categories and Qwen3-Coder 480B-A35B Instruct in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.4 Pro leads 71.0 to 24.7.
- The biggest single-benchmark swing is WeirdML: 57.4% for GPT-5.4 Pro and 41.2% for Qwen3-Coder 480B-A35B Instruct.
- Qwen3-Coder 480B-A35B Instruct is cheaper at $1.50 / $7.50 per million input/output tokens, against $30 / $180 for GPT-5.4 Pro.
- GPT-5.4 Pro accepts more context: 1.05M tokens versus 262K.
- Qwen3-Coder 480B-A35B Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 58.8 | 37.7 |
| Released | 2026-03-05 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $30 | $1.50 |
| Output $ / M tokens | $180 | $7.50 |
| Results tracked | 16 | 25 |
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Category by category
Coding GPT-5.4 Pro leads
GPT-5.4 Pro: 42.6 (#89), Qwen3-Coder 480B-A35B Instruct: 36.2 (#199)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 57.4% | 41.2% |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| GSO | — | 4.9% |
| LMArena Coding | — | 1413 |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
GPT-5.4 Pro: —, Qwen3-Coder 480B-A35B Instruct: 23.7 (#116)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning GPT-5.4 Pro leads
GPT-5.4 Pro: 71.0 (#10), Qwen3-Coder 480B-A35B Instruct: 24.7 (#141)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| ARC-AGI-2 | 83.3% | — |
| SimpleBench | 74.1% | — |
| Kagi LLM Benchmark | — | 49.5% |
| ARC-AGI-1 | 94.5% | — |
| CritPt | 30% | — |
| Chess Puzzles | 58.6% | — |
| EnigmaEval | 23.8% | — |
| LMArena Hard Prompts | — | 1372 |
| Epoch Capabilities Index | 159.12 | — |
Math GPT-5.4 Pro leads
GPT-5.4 Pro: 72.0 (#17), Qwen3-Coder 480B-A35B Instruct: 34.9 (#151)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 82.5% | — |
| FrontierMath Tier 4 | 58.5% | — |
| LMArena Math | — | 1364 |
| FrontierMath (Feb 2025 set) | 50% | — |
| FrontierMath Tier 4 (v1) | 37.5% | — |
Knowledge GPT-5.4 Pro leads
GPT-5.4 Pro: 68.3 (#6), Qwen3-Coder 480B-A35B Instruct: 36.4 (#159)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| GPQA Diamond | 94.6% | — |
| Humanity's Last Exam | 44.3% | — |
| SimpleQA Verified | 46.3% | — |
| Vectara Hallucination Rate | 8.3% | — |
| LMArena Expert | — | 1337 |
Multilingual Not comparable
GPT-5.4 Pro: —, Qwen3-Coder 480B-A35B Instruct: 47.8 (#143)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | — | 1345 |
| LMArena Chinese | — | 1356 |
| LMArena French | — | 1394 |
| LMArena German | — | 1324 |
| LMArena Japanese | — | 1309 |
| LMArena Korean | — | 1307 |
| LMArena Russian | — | 1367 |
| LMArena Spanish | — | 1360 |
Instruction Following Not comparable
GPT-5.4 Pro: —, Qwen3-Coder 480B-A35B Instruct: 71.8 (#142)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | — | 1356 |
Long Context Not comparable
GPT-5.4 Pro: —, Qwen3-Coder 480B-A35B Instruct: 42.0 (#126)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | — | 1379 |
Writing & Preference Not comparable
GPT-5.4 Pro: —, Qwen3-Coder 480B-A35B Instruct: 55.5 (#142)
| Benchmark | GPT-5.4 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | — | 1356 |
| LMArena Creative Writing | — | 1333 |
| LMArena Multi-Turn | — | 1365 |
Frequently asked questions
Is GPT-5.4 Pro better than Qwen3-Coder 480B-A35B Instruct?
GPT-5.4 Pro is the stronger model overall, scoring 58.8 to 37.7 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 23× less per token, which makes it the better buy when GPT-5.4 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.4 Pro or Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; GPT-5.4 Pro lists at $30 and $180.
Is GPT-5.4 Pro or Qwen3-Coder 480B-A35B Instruct better for coding?
GPT-5.4 Pro scores higher on coding benchmarks: 42.6 versus 36.2 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 Pro does, with 1.05M tokens against 262K.
How many benchmarks do GPT-5.4 Pro and Qwen3-Coder 480B-A35B Instruct share?
1 benchmark has published results for both models. GPT-5.4 Pro has 16 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.