Model comparison
Qwen1.5-14B vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 32.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3 14B leads 39.3 to 29.8.
Side by side
| Qwen1.5-14B | Qwen3 14B | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 32.7 | 35.5 |
| Released | 2024-02-04 | 2025-04 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $0.35 |
| Output $ / M tokens | — | $1.40 |
| Results tracked | 17 | 12 |
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Category by category
Coding Qwen3 14B leads
Qwen1.5-14B: 33.1 (#263), Qwen3 14B: 37.3 (#195)
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
| LMArena Coding | 1138 | — |
Agentic & Tool Use Not comparable
Qwen1.5-14B: —, Qwen3 14B: 29.6 (#83)
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Qwen1.5-14B leads
Qwen1.5-14B: 21.4 (#223), Qwen3 14B: 18.5 (#280)
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | — | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1113 | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Qwen3 14B leads
Qwen1.5-14B: 32.4 (#215), Qwen3 14B: 38.6 (#133)
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| LMArena Math | 1125 | — |
Knowledge Qwen3 14B leads
Qwen1.5-14B: 29.8 (#232), Qwen3 14B: 39.3 (#134)
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1094 | — |
| MMLU | 68.6% | — |
Multilingual Not comparable
Qwen1.5-14B: 30.7 (#262), Qwen3 14B: —
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1095 | — |
| LMArena Chinese | 1147 | — |
| LMArena French | 1116 | — |
| LMArena German | 1043 | — |
| LMArena Japanese | 1019 | — |
| LMArena Russian | 1046 | — |
| LMArena Spanish | 1085 | — |
Instruction Following Not comparable
Qwen1.5-14B: 56.8 (#271), Qwen3 14B: —
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1102 | — |
Long Context Qwen3 14B leads
Qwen1.5-14B: 33.7 (#257), Qwen3 14B: 38.1 (#204)
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1113 | — |
Writing & Preference Not comparable
Qwen1.5-14B: 33.6 (#276), Qwen3 14B: —
| Benchmark | Qwen1.5-14B | Qwen3 14B |
|---|---|---|
| LMArena Text | 1128 | — |
| LMArena Creative Writing | 1091 | — |
| LMArena Multi-Turn | 1110 | — |
Frequently asked questions
Is Qwen1.5-14B better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 32.7 on the Noometry Index.
Is Qwen1.5-14B or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 33.1 in the Noometry coding category.
How many benchmarks do Qwen1.5-14B and Qwen3 14B share?
0 benchmarks have published results for both models. Qwen1.5-14B has 17 scored results on Noometry and Qwen3 14B has 12.