Model comparison
o3-pro vs Qwen3.6 35B-A3B
o3-pro is the stronger model overall, scoring 42.9 to 37.6 on the Noometry Index. Qwen3.6 35B-A3B costs 63× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. o3-pro scores higher in 1 category and Qwen3.6 35B-A3B in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 35B-A3B leads 51.3 to 29.5.
- The biggest single-benchmark swing is WeirdML: 58.2% for o3-pro and 34.5% for Qwen3.6 35B-A3B.
- Qwen3.6 35B-A3B is cheaper at $0.25 / $1.49 per million input/output tokens, against $20 / $80 for o3-pro.
- Qwen3.6 35B-A3B accepts more context: 262K tokens versus 200K.
- Qwen3.6 35B-A3B has downloadable open weights; the other is API-only.
Side by side
| o3-pro | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.9 | 37.6 |
| Released | 2025-06-10 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 100K | 66K |
| Input $ / M tokens | $20 | $0.25 |
| Output $ / M tokens | $80 | $1.49 |
| Results tracked | 12 | 14 |
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Category by category
Coding o3-pro leads
o3-pro: 55.5 (#24), Qwen3.6 35B-A3B: 37.2 (#196)
| Benchmark | o3-pro | Qwen3.6 35B-A3B |
|---|---|---|
| WeirdML | 58.2% | 34.5% |
| Aider Polyglot | 84.9% | — |
| SciCode | — | 35.8% |
Agentic & Tool Use Not comparable
o3-pro: —, Qwen3.6 35B-A3B: 22.1 (#134)
| Benchmark | o3-pro | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
Reasoning Qwen3.6 35B-A3B leads
o3-pro: 23.8 (#171), Qwen3.6 35B-A3B: 28.0 (#109)
| Benchmark | o3-pro | Qwen3.6 35B-A3B |
|---|---|---|
| DTBench | 86.9% | 73.9% |
| LMCA | 38.5% | 29.7% |
| Epoch Capabilities Index | 147.42 | 143.93 |
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| NYT Connections (extended) | — | 41.6% |
| ARC-AGI-1 | 59.3% | — |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 26% |
| Mystery Game Puzzles | — | 22% |
| Surface Evolver Bench | — | 44.4% |
Math Not comparable
o3-pro: —, Qwen3.6 35B-A3B: 38.9 (#121)
| Benchmark | o3-pro | Qwen3.6 35B-A3B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 20.4% |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
Knowledge Qwen3.6 35B-A3B leads
o3-pro: 29.5 (#238), Qwen3.6 35B-A3B: 51.3 (#68)
| Benchmark | o3-pro | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | — | 84.8% |
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |
Long Context Not comparable
o3-pro: 72.2 (#1), Qwen3.6 35B-A3B: —
| Benchmark | o3-pro | Qwen3.6 35B-A3B |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |
Writing & Preference Not comparable
o3-pro: 57.1 (#133), Qwen3.6 35B-A3B: —
| Benchmark | o3-pro | Qwen3.6 35B-A3B |
|---|---|---|
| Short-Story Creative Writing | 84.4% | — |
Frequently asked questions
Is o3-pro better than Qwen3.6 35B-A3B?
o3-pro is the stronger model overall, scoring 42.9 to 37.6 on the Noometry Index. Qwen3.6 35B-A3B costs 63× 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 Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is cheaper. It lists at $0.25 per million input tokens and $1.49 per million output tokens; o3-pro lists at $20 and $80.
Is o3-pro or Qwen3.6 35B-A3B better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 37.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 35B-A3B does, with 262K tokens against 200K.
How many benchmarks do o3-pro and Qwen3.6 35B-A3B share?
4 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Qwen3.6 35B-A3B has 14.