# o1 vs Qwen2.5-Coder-32B

> o1 is the stronger model overall, scoring 40.9 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 35× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/o1-vs-qwen2-5-coder-32b
- Last updated: 2026-10-11
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. o1 scores higher in 8 categories and Qwen2.5-Coder-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where o1 leads 46.1 to 22.6.
- The biggest single-benchmark swing is LiveBench Reasoning: 91.6% for o1 and 42.1% for Qwen2.5-Coder-32B.
- Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $15 / $60 for o1.
- o1 accepts more context: 200K tokens versus 33K.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

## Snapshot

| | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 40.9 | 33.4 |
| Rank | 143 | 245 |
| Context | 200K | 33K |
| Input $/M | $15 | $0.66 |
| Output $/M | $60 | $1 |
| Weights | Proprietary | Open |

## Coding

- o1: 46.1 (#70)
- Qwen2.5-Coder-32B: 22.6 (#333)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| Aider Polyglot | 61.7% | 16.4% |
| LiveBench Coding | 69.7% | 56.9% |
| LMArena Coding | 1367 | 1276 |
| HumanEval+ | 89% | 87.2% |
| MBPP+ | 80.2% | 77% |
| SWE-bench Verified (bash only) | — | 9% |
| WeirdML | 47.6% | — |
| BigCodeBench Instruct | — | 49% |
| BigCodeBench Complete | — | 58% |
| CadEval | 56% | — |

## Agentic & Tool Use

- o1: 24.6 (#117)
- Qwen2.5-Coder-32B: —

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| Cybench | 10% | — |
| METR Time Horizons | 51.1% | — |

## Reasoning

- o1: 27.9 (#111)
- Qwen2.5-Coder-32B: 21.2 (#225)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Reasoning | 91.6% | 42.1% |
| LMArena Hard Prompts | 1371 | 1251 |
| LiveBench Data Analysis | 65.5% | 49.9% |
| Epoch Capabilities Index | 141.91 | 119.49 |
| LiveBench | 75.7% | 46.2% |
| SimpleBench | 41.7% | — |
| ARC-AGI-1 | 30.7% | — |
| Chess Puzzles | 15% | — |
| EnigmaEval | 5.7% | — |
| DTBench | 74.7% | — |
| LMCA | 22.3% | — |
| HellaSwag | — | 83% |
| WinoGrande | — | 80.8% |

## Math

- o1: 36.1 (#175)
- Qwen2.5-Coder-32B: 33.3 (#204)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Math | 80.3% | 46.6% |
| LMArena Math | 1388 | 1251 |
| FrontierMath (Tiers 1-3) | 14.7% | — |
| OTIS Mock AIME 2024-2025 | 73.3% | — |
| MATH Level 5 | 94.7% | — |
| FrontierMath (Feb 2025 set) | 9.3% | — |
| GSM8K | — | 93% |

## Knowledge

- o1: 41.5 (#110)
- Qwen2.5-Coder-32B: 33.4 (#203)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1361 | 1221 |
| GPQA Diamond | 76.8% | — |
| Humanity's Last Exam | 8% | — |
| SimpleQA Verified | 41.1% | — |
| Confabulations | 11.7% | — |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |

## Multimodal

- o1: 34.2 (#93)
- Qwen2.5-Coder-32B: —

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1168 | — |
| GeoBench | 80% | — |
| VPCT | 37% | — |
| SpatialViz-Bench | 41.4% | — |

## Multilingual

- o1: 48.6 (#142)
- Qwen2.5-Coder-32B: 37.8 (#235)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1358 | 1205 |
| LMArena Chinese | 1394 | 1222 |
| LMArena Russian | 1356 | 1228 |
| LMArena French | 1344 | — |
| LMArena German | 1337 | — |
| LMArena Japanese | 1346 | — |
| LMArena Korean | 1396 | — |
| LMArena Spanish | 1345 | — |

## Instruction Following

- o1: 74.8 (#86)
- Qwen2.5-Coder-32B: 61.4 (#245)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LiveBench Instruction Following | 81.5% | 58.7% |
| LMArena Instruction Following | 1367 | 1223 |

## Long Context

- o1: 50.3 (#9)
- Qwen2.5-Coder-32B: 38.0 (#208)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1378 | 1251 |
| Fiction.LiveBench | 83.3% | — |

## Writing & Preference

- o1: 55.6 (#144)
- Qwen2.5-Coder-32B: 41.6 (#240)

| Benchmark | o1 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1366 | 1230 |
| LMArena Creative Writing | 1348 | 1174 |
| LMArena Multi-Turn | 1369 | 1222 |
| LiveBench Language | 65.4% | 23.3% |
| Short-Story Creative Writing | 70.2% | — |

## FAQ

### Is o1 better than Qwen2.5-Coder-32B?

o1 is the stronger model overall, scoring 40.9 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 35× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.

### Which is cheaper, o1 or Qwen2.5-Coder-32B?

Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; o1 lists at $15 and $60.

### Is o1 or Qwen2.5-Coder-32B better for coding?

o1 scores higher on coding benchmarks: 46.1 versus 22.6 in the Noometry coding category.

### Which has the bigger context window?

o1 does, with 200K tokens against 33K.

### How many benchmarks do o1 and Qwen2.5-Coder-32B share?

23 benchmarks have published results for both models. o1 has 52 scored results on Noometry and Qwen2.5-Coder-32B has 31.