Model comparison
o3-pro vs Qwen3-Coder 480B-A35B Instruct
o3-pro is the stronger model overall, scoring 42.9 to 38.1 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 12× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. o3-pro scores higher in 3 categories and Qwen3-Coder 480B-A35B Instruct in 2 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 42.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 72.1% for o3-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 $20 / $80 for o3-pro.
- Qwen3-Coder 480B-A35B Instruct accepts more context: 262K tokens versus 200K.
- Qwen3-Coder 480B-A35B Instruct has downloadable open weights; the other is API-only.
Side by side
| o3-pro | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.9 | 38.1 |
| Released | 2025-06-10 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 100K | 66K |
| Input $ / M tokens | $20 | $1.50 |
| Output $ / M tokens | $80 | $7.50 |
| Results tracked | 12 | 25 |
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Category by category
Coding o3-pro leads
o3-pro: 55.5 (#24), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 58.2% | 41.2% |
| SWE-bench Verified (bash only) | — | 55.4% |
| Aider Polyglot | 84.9% | — |
| LMArena WebDev | — | 1275 |
| GSO | — | 4.9% |
| LMArena Coding | — | 1412 |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
o3-pro: —, Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning Qwen3-Coder 480B-A35B Instruct leads
o3-pro: 23.8 (#171), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 72.1% | 49.5% |
| ARC-AGI-2 | 4.9% | — |
| ARC-AGI-1 | 59.3% | — |
| LMArena Hard Prompts | — | 1372 |
| DTBench | 86.9% | — |
| LMCA | 38.5% | — |
| Epoch Capabilities Index | 147.42 | — |
Math Not comparable
o3-pro: —, Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | — | 1365 |
Knowledge Qwen3-Coder 480B-A35B Instruct leads
o3-pro: 29.5 (#238), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |
| LMArena Expert | — | 1338 |
Multilingual Not comparable
o3-pro: —, Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | o3-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
o3-pro: —, Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | — | 1355 |
Long Context o3-pro leads
o3-pro: 72.2 (#1), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |
| LMArena Longer Query | — | 1378 |
Writing & Preference o3-pro leads
o3-pro: 57.1 (#133), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | o3-pro | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | — | 1357 |
| LMArena Creative Writing | — | 1333 |
| Short-Story Creative Writing | 84.4% | — |
| LMArena Multi-Turn | — | 1365 |
Frequently asked questions
Is o3-pro better than Qwen3-Coder 480B-A35B Instruct?
o3-pro is the stronger model overall, scoring 42.9 to 38.1 on the Noometry Index. Qwen3-Coder 480B-A35B Instruct costs 12× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, o3-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; o3-pro lists at $20 and $80.
Is o3-pro or Qwen3-Coder 480B-A35B Instruct better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Coder 480B-A35B Instruct does, with 262K tokens against 200K.
How many benchmarks do o3-pro and Qwen3-Coder 480B-A35B Instruct share?
2 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.