Model comparison
GPT-5 Pro vs Qwen3-Coder 480B-A35B Instruct
GPT-5 Pro is the stronger model overall, scoring 46.4 to 38.1 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 14× less per token, which makes it the better buy when GPT-5 Pro's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. GPT-5 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 knowledge, where GPT-5 Pro leads 56.7 to 37.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 76.8% for GPT-5 Pro and 49.5% for Qwen3-Coder 480B-A35B Instruct.
- Qwen3-Coder 480B-A35B Instruct is cheaper at $1.50 / $7.50 per million input/output tokens, against $15 / $120 for GPT-5 Pro.
- GPT-5 Pro 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 Pro | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 46.4 | 38.1 |
| Released | 2025-10-06 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 272K | 66K |
| Input $ / M tokens | $15 | $1.50 |
| Output $ / M tokens | $120 | $7.50 |
| Results tracked | 12 | 25 |
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Category by category
Coding GPT-5 Pro leads
GPT-5 Pro: 44.0 (#80), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 60.4% | 41.2% |
| AlgoTune | 1.31 | 1.44 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| GSO | — | 4.9% |
| LMArena Coding | — | 1412 |
| ALE-Bench | — | 461.45 |
Agentic & Tool Use Not comparable
GPT-5 Pro: —, Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning GPT-5 Pro leads
GPT-5 Pro: 38.9 (#62), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 76.8% | 49.5% |
| ARC-AGI-2 | 18.3% | — |
| SimpleBench | 61.6% | — |
| ARC-AGI-1 | 70.2% | — |
| EnigmaEval | 18.8% | — |
| LMArena Hard Prompts | — | 1372 |
| Epoch Capabilities Index | 150.28 | — |
Math GPT-5 Pro leads
GPT-5 Pro: 48.5 (#63), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 19.5% | — |
| LMArena Math | — | 1365 |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge GPT-5 Pro leads
GPT-5 Pro: 56.7 (#42), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Humanity's Last Exam | 31.6% | — |
| LMArena Expert | — | 1338 |
Multilingual Not comparable
GPT-5 Pro: —, Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | — | 1346 |
| LMArena Chinese | — | 1357 |
| LMArena French | — | 1398 |
| LMArena German | — | 1325 |
| LMArena Japanese | — | 1310 |
| LMArena Korean | — | 1305 |
| LMArena Russian | — | 1366 |
| LMArena Spanish | — | 1360 |
Instruction Following Not comparable
GPT-5 Pro: —, Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | — | 1355 |
Long Context Not comparable
GPT-5 Pro: —, Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | — | 1378 |
Writing & Preference Not comparable
GPT-5 Pro: —, Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | GPT-5 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | — | 1357 |
| LMArena Creative Writing | — | 1333 |
| LMArena Multi-Turn | — | 1365 |
Frequently asked questions
Is GPT-5 Pro better than Qwen3-Coder 480B-A35B Instruct?
GPT-5 Pro is the stronger model overall, scoring 46.4 to 38.1 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 14× less per token, which makes it the better buy when GPT-5 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5 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 Pro lists at $15 and $120.
Is GPT-5 Pro or Qwen3-Coder 480B-A35B Instruct better for coding?
GPT-5 Pro scores higher on coding benchmarks: 44.0 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5 Pro does, with 400K tokens against 262K.
How many benchmarks do GPT-5 Pro and Qwen3-Coder 480B-A35B Instruct share?
3 benchmarks have published results for both models. GPT-5 Pro has 12 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.