# o3-pro vs Qwen3.5-9B

> o3-pro is the stronger model overall, scoring 42.7 to 33.3 on the Noometry Index. Qwen3.5-9B costs 311× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/o3-pro-vs-qwen3-5-9b
- Last updated: 2026-10-10
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. o3-pro scores higher in 2 categories and Qwen3.5-9B in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in coding, where o3-pro leads 55.1 to 35.3.
- The biggest single-benchmark swing is DTBench: 86.9% for o3-pro and 71.2% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $20 / $80 for o3-pro.
- Qwen3.5-9B accepts more context: 262K tokens versus 200K.
- Qwen3.5-9B has downloadable open weights; the other is API-only.

## Snapshot

| | o3-pro | Qwen3.5-9B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.7 | 33.3 |
| Rank | 94 | 235 |
| Context | 200K | 262K |
| Input $/M | $20 | $0.10 |
| Output $/M | $80 | $0.15 |
| Weights | Proprietary | Open |

## Coding

- o3-pro: 55.1 (#22)
- Qwen3.5-9B: 35.3 (#213)

| Benchmark | o3-pro | Qwen3.5-9B |
|---|---|---|
| Aider Polyglot | 84.9% | — |
| SciCode | — | 27.5% |
| WeirdML | 58.2% | — |

## Agentic & Tool Use

- o3-pro: —
- Qwen3.5-9B: 14.4 (#143)

| Benchmark | o3-pro | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | — | 9.2% |

## Reasoning

- o3-pro: 24.1 (#152)
- Qwen3.5-9B: 22.5 (#178)

| Benchmark | o3-pro | Qwen3.5-9B |
|---|---|---|
| DTBench | 86.9% | 71.2% |
| LMCA | 38.5% | 24.5% |
| Epoch Capabilities Index | 147.43 | 139.45 |
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| ARC-AGI-1 | 59.3% | — |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 12% |

## Math

- o3-pro: —
- Qwen3.5-9B: 33.5 (#174)

| Benchmark | o3-pro | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 48.5% |
| OTIS Mock AIME 2024-2025 | — | 61.7% |

## Knowledge

- o3-pro: 29.0 (#234)
- Qwen3.5-9B: 46.0 (#77)

| Benchmark | o3-pro | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | — | 79% |
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |

## Long Context

- o3-pro: 72.1 (#1)
- Qwen3.5-9B: —

| Benchmark | o3-pro | Qwen3.5-9B |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |

## Writing & Preference

- o3-pro: 57.1 (#128)
- Qwen3.5-9B: —

| Benchmark | o3-pro | Qwen3.5-9B |
|---|---|---|
| Short-Story Creative Writing | 84.4% | — |

## FAQ

### Is o3-pro better than Qwen3.5-9B?

o3-pro is the stronger model overall, scoring 42.7 to 33.3 on the Noometry Index. Qwen3.5-9B costs 311× 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 Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; o3-pro lists at $20 and $80.

### Is o3-pro or Qwen3.5-9B better for coding?

o3-pro scores higher on coding benchmarks: 55.1 versus 35.3 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 200K.

### How many benchmarks do o3-pro and Qwen3.5-9B share?

3 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Qwen3.5-9B has 10.