Model comparison
o3-pro vs Yi-34B
o3-pro is the stronger model overall, scoring 42.9 to 27.8 on the Noometry Index.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. o3-pro scores higher in 5 categories and Yi-34B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 33.2.
- Yi-34B has downloadable open weights; the other is API-only.
Side by side
| o3-pro | Yi-34B | |
|---|---|---|
| Provider | OpenAI | 01.AI |
| Noometry Index | 42.9 | 27.8 |
| Released | 2025-06-10 | 2023-11-02 |
| Weights | Proprietary | Open |
| Context window | 200K | — |
| Max output | 100K | — |
| Input $ / M tokens | $20 | — |
| Output $ / M tokens | $80 | — |
| Results tracked | 12 | 23 |
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Category by category
Coding o3-pro leads
o3-pro: 55.5 (#24), Yi-34B: 32.3 (#274)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| Aider Polyglot | 84.9% | — |
| WeirdML | 58.2% | — |
| LMArena Coding | — | 1112 |
Reasoning o3-pro leads
o3-pro: 23.8 (#171), Yi-34B: 21.2 (#226)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| Epoch Capabilities Index | 147.42 | 117.39 |
| ARC-AGI-2 | 4.9% | — |
| Kagi LLM Benchmark | 72.1% | — |
| ARC-AGI-1 | 59.3% | — |
| LMArena Hard Prompts | — | 1104 |
| DTBench | 86.9% | — |
| LMCA | 38.5% | — |
| BIG-Bench Hard | — | 71.7% |
Math Not comparable
o3-pro: —, Yi-34B: 21.6 (#282)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| LMArena Math | — | 1114 |
| MATH Level 5 | — | 5.1% |
| GSM8K | — | 76% |
Knowledge o3-pro leads
o3-pro: 29.5 (#238), Yi-34B: 7.5 (#309)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| GPQA Diamond | — | 14.7% |
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 23.3% | — |
| LMArena Expert | — | 1061 |
| MMLU | — | 76.3% |
Multilingual Not comparable
o3-pro: —, Yi-34B: 29.7 (#264)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| LMArena Non-English | — | 1079 |
| LMArena Chinese | — | 1176 |
| LMArena French | — | 1081 |
| LMArena German | — | 1042 |
| LMArena Japanese | — | 993 |
| LMArena Korean | — | 959 |
| LMArena Russian | — | 1050 |
| LMArena Spanish | — | 1070 |
Instruction Following Not comparable
o3-pro: —, Yi-34B: 56.2 (#274)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| LMArena Instruction Following | — | 1091 |
Long Context o3-pro leads
o3-pro: 72.2 (#1), Yi-34B: 33.2 (#264)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| Fiction.LiveBench | 97.2% | — |
| LMArena Longer Query | — | 1094 |
Writing & Preference o3-pro leads
o3-pro: 57.1 (#133), Yi-34B: 34.1 (#273)
| Benchmark | o3-pro | Yi-34B |
|---|---|---|
| LMArena Text | — | 1129 |
| LMArena Creative Writing | — | 1108 |
| Short-Story Creative Writing | 84.4% | — |
| LMArena Multi-Turn | — | 1113 |
Frequently asked questions
Is o3-pro better than Yi-34B?
o3-pro is the stronger model overall, scoring 42.9 to 27.8 on the Noometry Index.
Is o3-pro or Yi-34B better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 32.3 in the Noometry coding category.
How many benchmarks do o3-pro and Yi-34B share?
1 benchmark has published results for both models. o3-pro has 12 scored results on Noometry and Yi-34B has 23.