Model comparison
Qwen3 14B vs Yi-Lightning
Yi-Lightning is the stronger model overall, scoring 36.5 to 35.0 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in coding, where Qwen3 14B leads 36.7 to 27.0.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| Qwen3 14B | Yi-Lightning | |
|---|---|---|
| Provider | Alibaba (Qwen) | 01.AI |
| Noometry Index | 35.0 | 36.5 |
| Released | 2025-04 | 2024-12-02 |
| Weights | Open | Proprietary |
| Context window | 131K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.35 | — |
| Output $ / M tokens | $1.40 | — |
| Results tracked | 12 | 18 |
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Category by category
Coding Qwen3 14B leads
Qwen3 14B: 36.7 (#191), Yi-Lightning: 27.0 (#315)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| Aider Polyglot | — | 12.9% |
| SciCode | 31.6% | — |
| LMArena Coding | — | 1313 |
Agentic & Tool Use Not comparable
Qwen3 14B: 29.4 (#78), Yi-Lightning: —
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| Berkeley Function Calling Leaderboard | 41% | — |
Reasoning Yi-Lightning leads
Qwen3 14B: 18.1 (#272), Yi-Lightning: 24.9 (#137)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| Kagi LLM Benchmark | 49.1% | — |
| CritPt | 0% | — |
| Chess Puzzles | 4% | — |
| LMArena Hard Prompts | — | 1302 |
| DTBench | 64% | — |
| LMCA | 18.2% | — |
| Epoch Capabilities Index | 138.23 | — |
Math Qwen3 14B leads
Qwen3 14B: 37.0 (#102), Yi-Lightning: 33.5 (#173)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.4% | — |
| LMArena Math | — | 1300 |
Knowledge Qwen3 14B leads
Qwen3 14B: 39.2 (#124), Yi-Lightning: 34.8 (#182)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| GPQA Diamond | 63.8% | — |
| Vectara Hallucination Rate | 5.4% | — |
| LMArena Expert | — | 1286 |
Multilingual Not comparable
Qwen3 14B: —, Yi-Lightning: 42.4 (#191)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| LMArena Non-English | — | 1269 |
| LMArena Chinese | — | 1320 |
| LMArena French | — | 1304 |
| LMArena German | — | 1267 |
| LMArena Japanese | — | 1228 |
| LMArena Korean | — | 1192 |
| LMArena Russian | — | 1255 |
| LMArena Spanish | — | 1315 |
Instruction Following Not comparable
Qwen3 14B: —, Yi-Lightning: 67.6 (#191)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| LMArena Instruction Following | — | 1278 |
Long Context Yi-Lightning leads
Qwen3 14B: 38.0 (#201), Yi-Lightning: 39.4 (#176)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| Fiction.LiveBench | 62.5% | — |
| LMArena Longer Query | — | 1297 |
Writing & Preference Not comparable
Qwen3 14B: —, Yi-Lightning: 50.4 (#178)
| Benchmark | Qwen3 14B | Yi-Lightning |
|---|---|---|
| LMArena Text | — | 1302 |
| LMArena Creative Writing | — | 1280 |
| LMArena Multi-Turn | — | 1311 |
Frequently asked questions
Is Qwen3 14B better than Yi-Lightning?
Yi-Lightning is the stronger model overall, scoring 36.5 to 35.0 on the Noometry Index.
Is Qwen3 14B or Yi-Lightning better for coding?
Qwen3 14B scores higher on coding benchmarks: 36.7 versus 27.0 in the Noometry coding category.
How many benchmarks do Qwen3 14B and Yi-Lightning share?
0 benchmarks have published results for both models. Qwen3 14B has 12 scored results on Noometry and Yi-Lightning has 18.