# o3-pro vs Yi-1.5-34B

> o3-pro is the stronger model overall, scoring 42.7 to 30.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/o3-pro-vs-yi-1-5-34b
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in long context, where o3-pro leads 72.1 to 34.6.
- Yi-1.5-34B has downloadable open weights; the other is API-only.

## Snapshot

| | o3-pro | Yi-1.5-34B |
|---|---|---|
| Provider | OpenAI | 01.AI |
| Noometry Index | 42.7 | 30.2 |
| Rank | 94 | 286 |
| Context | 200K | — |
| Input $/M | $20 | — |
| Output $/M | $80 | — |
| Weights | Proprietary | Open |

## Coding

- o3-pro: 55.1 (#22)
- Yi-1.5-34B: 31.9 (#267)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| Aider Polyglot | 84.9% | — |
| WeirdML | 58.2% | — |
| BigCodeBench Instruct | — | 33.9% |
| LMArena Coding | — | 1169 |
| BigCodeBench Complete | — | 43.8% |

## Reasoning

- o3-pro: 24.1 (#152)
- Yi-1.5-34B: 21.5 (#195)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| ARC-AGI-1 | 59.3% | — |
| LMArena Hard Prompts | — | 1160 |
| DTBench | 86.9% | — |
| LMCA | 38.5% | — |
| Epoch Capabilities Index | 147.43 | — |

## Math

- o3-pro: —
- Yi-1.5-34B: 25.3 (#248)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| LMArena Math | — | 1182 |
| MATH Level 5 | — | 25.5% |

## Knowledge

- o3-pro: 29.0 (#234)
- Yi-1.5-34B: 14.8 (#290)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| GPQA Diamond | — | 32% |
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |
| LMArena Expert | — | 1144 |

## Multilingual

- o3-pro: —
- Yi-1.5-34B: 32.5 (#251)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| LMArena Non-English | — | 1121 |
| LMArena Chinese | — | 1213 |
| LMArena French | — | 1155 |
| LMArena German | — | 1111 |
| LMArena Japanese | — | 1021 |
| LMArena Korean | — | 1005 |
| LMArena Russian | — | 1091 |
| LMArena Spanish | — | 1120 |

## Instruction Following

- o3-pro: —
- Yi-1.5-34B: 59.4 (#252)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| LMArena Instruction Following | — | 1139 |

## Long Context

- o3-pro: 72.1 (#1)
- Yi-1.5-34B: 34.6 (#243)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |
| LMArena Longer Query | — | 1144 |

## Writing & Preference

- o3-pro: 57.1 (#128)
- Yi-1.5-34B: 37.6 (#252)

| Benchmark | o3-pro | Yi-1.5-34B |
|---|---|---|
| LMArena Text | — | 1173 |
| LMArena Creative Writing | — | 1135 |
| Short-Story Creative Writing | 84.4% | — |
| LMArena Multi-Turn | — | 1153 |

## FAQ

### Is o3-pro better than Yi-1.5-34B?

o3-pro is the stronger model overall, scoring 42.7 to 30.2 on the Noometry Index.

### Is o3-pro or Yi-1.5-34B better for coding?

o3-pro scores higher on coding benchmarks: 55.1 versus 31.9 in the Noometry coding category.

### How many benchmarks do o3-pro and Yi-1.5-34B share?

0 benchmarks have published results for both models. o3-pro has 12 scored results on Noometry and Yi-1.5-34B has 21.