Model comparison
Qwen3 14B vs Yi-1.5-34B
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.6 on the Noometry Index.
Last verified . 1 shared benchmarks.
Alibaba (Qwen)Summary
- They share 1 benchmark with published results for both. Qwen3 14B scores higher in 4 categories and Yi-1.5-34B in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 14B leads 39.3 to 14.8.
- The biggest single-benchmark swing is GPQA Diamond: 63.8% for Qwen3 14B and 32% for Yi-1.5-34B.
Side by side
| Qwen3 14B | Yi-1.5-34B | |
|---|---|---|
| Provider | Alibaba (Qwen) | 01.AI |
| Noometry Index | 35.5 | 30.6 |
| Released | 2025-04 | 2024-05-13 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.35 | — |
| Output $ / M tokens | $1.40 | — |
| Results tracked | 12 | 21 |
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Category by category
Coding Qwen3 14B leads
Qwen3 14B: 37.3 (#195), Yi-1.5-34B: 32.4 (#272)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| SciCode | 31.6% | — |
| BigCodeBench Instruct | — | 33.9% |
| LMArena Coding | — | 1169 |
| BigCodeBench Complete | — | 43.8% |
Agentic & Tool Use Not comparable
Qwen3 14B: 29.6 (#83), Yi-1.5-34B: —
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 41% | — |
Reasoning Yi-1.5-34B leads
Qwen3 14B: 18.5 (#280), Yi-1.5-34B: 22.5 (#191)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| Kagi LLM Benchmark | 49.1% | — |
| CritPt | 0% | — |
| Chess Puzzles | 4% | — |
| LMArena Hard Prompts | — | 1160 |
| DTBench | 64% | — |
| LMCA | 18.2% | — |
| Epoch Capabilities Index | 138.23 | — |
Math Qwen3 14B leads
Qwen3 14B: 38.6 (#133), Yi-1.5-34B: 27.5 (#249)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.4% | — |
| LMArena Math | — | 1182 |
| MATH Level 5 | — | 25.5% |
Knowledge Qwen3 14B leads
Qwen3 14B: 39.3 (#134), Yi-1.5-34B: 14.8 (#295)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| GPQA Diamond | 63.8% | 32% |
| Vectara Hallucination Rate | 5.4% | — |
| LMArena Expert | — | 1144 |
Multilingual Not comparable
Qwen3 14B: —, Yi-1.5-34B: 32.3 (#256)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| LMArena Non-English | — | 1121 |
| LMArena Chinese | — | 1213 |
| LMArena French | — | 1156 |
| LMArena German | — | 1111 |
| LMArena Japanese | — | 1021 |
| LMArena Korean | — | 1005 |
| LMArena Russian | — | 1091 |
| LMArena Spanish | — | 1121 |
Instruction Following Not comparable
Qwen3 14B: —, Yi-1.5-34B: 59.2 (#257)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| LMArena Instruction Following | — | 1139 |
Long Context Qwen3 14B leads
Qwen3 14B: 38.1 (#204), Yi-1.5-34B: 34.6 (#248)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| Fiction.LiveBench | 62.5% | — |
| LMArena Longer Query | — | 1143 |
Writing & Preference Not comparable
Qwen3 14B: —, Yi-1.5-34B: 37.4 (#257)
| Benchmark | Qwen3 14B | Yi-1.5-34B |
|---|---|---|
| LMArena Text | — | 1173 |
| LMArena Creative Writing | — | 1135 |
| LMArena Multi-Turn | — | 1153 |
Frequently asked questions
Is Qwen3 14B better than Yi-1.5-34B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.6 on the Noometry Index.
Is Qwen3 14B or Yi-1.5-34B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 32.4 in the Noometry coding category.
How many benchmarks do Qwen3 14B and Yi-1.5-34B share?
1 benchmark has published results for both models. Qwen3 14B has 12 scored results on Noometry and Yi-1.5-34B has 21.