Model comparison
GPT-5.2 Pro vs Qwen3-Coder 480B-A35B Instruct
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 38.1 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 19× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in math, where GPT-5.2 Pro leads 65.3 to 37.6.
- Qwen3-Coder 480B-A35B Instruct is cheaper at $1.50 / $7.50 per million input/output tokens, against $21 / $168 for GPT-5.2 Pro.
- GPT-5.2 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-5.2 Pro | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 52.3 | 38.1 |
| Released | 2025-12-11 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $21 | $1.50 |
| Output $ / M tokens | $168 | $7.50 |
| Results tracked | 8 | 25 |
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Category by category
Coding Not comparable
GPT-5.2 Pro: —, Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| LMArena Coding | — | 1412 |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
GPT-5.2 Pro: —, Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning GPT-5.2 Pro leads
GPT-5.2 Pro: 51.5 (#33), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| ARC-AGI-2 | 54.2% | — |
| SimpleBench | 57.4% | — |
| Kagi LLM Benchmark | — | 49.5% |
| NYT Connections (extended) | 79.3% | — |
| ARC-AGI-1 | 90.5% | — |
| LMArena Hard Prompts | — | 1372 |
| Epoch Capabilities Index | 155.4 | — |
Math GPT-5.2 Pro leads
GPT-5.2 Pro: 65.3 (#29), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 74% | — |
| FrontierMath Tier 4 | 46% | — |
| LMArena Math | — | 1365 |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Not comparable
GPT-5.2 Pro: —, Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | — | 1338 |
Multilingual Not comparable
GPT-5.2 Pro: —, Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | GPT-5.2 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-5.2 Pro: —, Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | — | 1355 |
Long Context Not comparable
GPT-5.2 Pro: —, Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | — | 1378 |
Writing & Preference Not comparable
GPT-5.2 Pro: —, Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | GPT-5.2 Pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | — | 1357 |
| LMArena Creative Writing | — | 1333 |
| LMArena Multi-Turn | — | 1365 |
Frequently asked questions
Is GPT-5.2 Pro better than Qwen3-Coder 480B-A35B Instruct?
GPT-5.2 Pro is the stronger model overall, scoring 52.3 to 38.1 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 19× less per token, which makes it the better buy when GPT-5.2 Pro's lead doesn't matter for your workload.
Which is cheaper, GPT-5.2 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-5.2 Pro lists at $21 and $168.
Which has the bigger context window?
GPT-5.2 Pro does, with 400K tokens against 262K.
How many benchmarks do GPT-5.2 Pro and Qwen3-Coder 480B-A35B Instruct share?
0 benchmarks have published results for both models. GPT-5.2 Pro has 8 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.