Model comparison
o3-pro vs Qwen3 8B
o3-pro is the stronger model overall, scoring 42.9 to 33.7 on the Noometry Index. Qwen3 8B costs 113× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 5 shared benchmarks.
Alibaba (Qwen)Summary
- They share 5 benchmarks with published results for both. o3-pro scores higher in 3 categories and Qwen3 8B in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 37.9.
- The biggest single-benchmark swing is Fiction.LiveBench: 97.2% for o3-pro and 62.1% for Qwen3 8B.
- Qwen3 8B is cheaper at $0.18 / $0.70 per million input/output tokens, against $20 / $80 for o3-pro.
- o3-pro accepts more context: 200K tokens versus 131K.
- Qwen3 8B has downloadable open weights; the other is API-only.
Side by side
| o3-pro | Qwen3 8B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.9 | 33.7 |
| Released | 2025-06-10 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 100K | 8K |
| Input $ / M tokens | $20 | $0.18 |
| Output $ / M tokens | $80 | $0.70 |
| Results tracked | 12 | 11 |
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Category by category
Coding o3-pro leads
o3-pro: 55.5 (#24), Qwen3 8B: 34.0 (#248)
| Benchmark | o3-pro | Qwen3 8B |
|---|---|---|
| Aider Polyglot | 84.9% | — |
| SciCode | — | 22.6% |
| WeirdML | 58.2% | — |
Agentic & Tool Use Not comparable
o3-pro: —, Qwen3 8B: 30.2 (#78)
| Benchmark | o3-pro | Qwen3 8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 42.6% |
Reasoning o3-pro leads
o3-pro: 23.8 (#171), Qwen3 8B: 16.6 (#303)
| Benchmark | o3-pro | Qwen3 8B |
|---|---|---|
| DTBench | 86.9% | 59.7% |
| LMCA | 38.5% | 8.8% |
| Epoch Capabilities Index | 147.42 | 136.17 |
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| ARC-AGI-1 | 59.3% | — |
| CritPt | — | 0% |
| Chess Puzzles | — | 5% |
Math Not comparable
o3-pro: —, Qwen3 8B: 34.9 (#191)
| Benchmark | o3-pro | Qwen3 8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 56.1% |
Knowledge Qwen3 8B leads
o3-pro: 29.5 (#238), Qwen3 8B: 36.1 (#173)
| Benchmark | o3-pro | Qwen3 8B |
|---|---|---|
| Vectara Hallucination Rate | 23.3% | 4.8% |
| GPQA Diamond | — | 56.8% |
| Confabulations | 14.2% | — |
Long Context o3-pro leads
o3-pro: 72.2 (#1), Qwen3 8B: 37.9 (#210)
| Benchmark | o3-pro | Qwen3 8B |
|---|---|---|
| Fiction.LiveBench | 97.2% | 62.1% |
Writing & Preference Not comparable
o3-pro: 57.1 (#133), Qwen3 8B: —
| Benchmark | o3-pro | Qwen3 8B |
|---|---|---|
| Short-Story Creative Writing | 84.4% | — |
Frequently asked questions
Is o3-pro better than Qwen3 8B?
o3-pro is the stronger model overall, scoring 42.9 to 33.7 on the Noometry Index. Qwen3 8B costs 113× 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 8B?
Qwen3 8B is cheaper. It lists at $0.18 per million input tokens and $0.70 per million output tokens; o3-pro lists at $20 and $80.
Is o3-pro or Qwen3 8B better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
o3-pro does, with 200K tokens against 131K.
How many benchmarks do o3-pro and Qwen3 8B share?
5 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Qwen3 8B has 11.