Model comparison
Qwen2.5-Max vs Yi-1.5-34B
Qwen2.5-Max is the stronger model overall, scoring 40.1 to 30.2 on the Noometry Index.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Qwen2.5-Max scores higher in 8 categories and Yi-1.5-34B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen2.5-Max leads 34.8 to 14.8.
- Yi-1.5-34B has downloadable open weights; the other is API-only.
Side by side
| Qwen2.5-Max | Yi-1.5-34B | |
|---|---|---|
| Provider | Alibaba (Qwen) | 01.AI |
| Noometry Index | 40.1 | 30.2 |
| Released | 2025-01-25 | 2024-05-13 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 27 | 21 |
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Category by category
Coding Qwen2.5-Max leads
Qwen2.5-Max: 41.2 (#118), Yi-1.5-34B: 31.9 (#267)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Coding | 1359 | 1169 |
| BigCodeBench Instruct | — | 33.9% |
| LiveBench Coding | 64.4% | — |
| BigCodeBench Complete | — | 43.8% |
Reasoning Qwen2.5-Max leads
Qwen2.5-Max: 24.6 (#144), Yi-1.5-34B: 21.5 (#195)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Hard Prompts | 1360 | 1160 |
| LiveBench Reasoning | 51.4% | — |
| LiveBench Data Analysis | 67.9% | — |
| Epoch Capabilities Index | 132.54 | — |
| LiveBench | 62.3% | — |
Math Qwen2.5-Max leads
Qwen2.5-Max: 34.3 (#162), Yi-1.5-34B: 25.3 (#248)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Math | 1369 | 1182 |
| LiveBench Math | 58.4% | — |
| MATH Level 5 | — | 25.5% |
Knowledge Qwen2.5-Max leads
Qwen2.5-Max: 34.8 (#181), Yi-1.5-34B: 14.8 (#290)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Expert | 1337 | 1144 |
| GPQA Diamond | — | 32% |
| Confabulations | 21.8% | — |
Multilingual Qwen2.5-Max leads
Qwen2.5-Max: 48.3 (#140), Yi-1.5-34B: 32.5 (#251)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Non-English | 1352 | 1121 |
| LMArena Chinese | 1382 | 1213 |
| LMArena French | 1396 | 1155 |
| LMArena German | 1350 | 1111 |
| LMArena Japanese | 1299 | 1021 |
| LMArena Korean | 1304 | 1005 |
| LMArena Russian | 1353 | 1091 |
| LMArena Spanish | 1377 | 1120 |
Instruction Following Qwen2.5-Max leads
Qwen2.5-Max: 71.5 (#147), Yi-1.5-34B: 59.4 (#252)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Instruction Following | 1335 | 1139 |
| LiveBench Instruction Following | 75.3% | — |
Long Context Qwen2.5-Max leads
Qwen2.5-Max: 41.3 (#137), Yi-1.5-34B: 34.6 (#243)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Longer Query | 1358 | 1144 |
Writing & Preference Qwen2.5-Max leads
Qwen2.5-Max: 55.6 (#141), Yi-1.5-34B: 37.6 (#252)
| Benchmark | Qwen2.5-Max | Yi-1.5-34B |
|---|---|---|
| LMArena Text | 1367 | 1173 |
| LMArena Creative Writing | 1339 | 1135 |
| LMArena Multi-Turn | 1364 | 1153 |
| Short-Story Creative Writing | 72.9% | — |
| LiveBench Language | 56.3% | — |
Frequently asked questions
Is Qwen2.5-Max better than Yi-1.5-34B?
Qwen2.5-Max is the stronger model overall, scoring 40.1 to 30.2 on the Noometry Index.
Is Qwen2.5-Max or Yi-1.5-34B better for coding?
Qwen2.5-Max scores higher on coding benchmarks: 41.2 versus 31.9 in the Noometry coding category.
How many benchmarks do Qwen2.5-Max and Yi-1.5-34B share?
17 benchmarks have published results for both models. Qwen2.5-Max has 27 scored results on Noometry and Yi-1.5-34B has 21.