Model comparison
Qwen1.5-32B vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.5 on the Noometry Index.
Last verified . 1 shared benchmarks.
Alibaba (Qwen)Summary
- They share 1 benchmark with published results for both. Qwen1.5-32B scores higher in 1 category and Qwen3 14B in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 14B leads 39.3 to 13.5.
- The biggest single-benchmark swing is GPQA Diamond: 30.7% for Qwen1.5-32B and 63.8% for Qwen3 14B.
Side by side
| Qwen1.5-32B | Qwen3 14B | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 30.5 | 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 | 21 | 12 |
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Category by category
Coding Qwen3 14B leads
Qwen1.5-32B: 31.7 (#282), Qwen3 14B: 37.3 (#195)
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
| BigCodeBench Instruct | 32.3% | — |
| LMArena Coding | 1155 | — |
| BigCodeBench Complete | 42% | — |
Agentic & Tool Use Not comparable
Qwen1.5-32B: —, Qwen3 14B: 29.6 (#83)
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Qwen1.5-32B leads
Qwen1.5-32B: 21.8 (#212), Qwen3 14B: 18.5 (#280)
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | — | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1130 | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Qwen3 14B leads
Qwen1.5-32B: 33.0 (#207), Qwen3 14B: 38.6 (#133)
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| LMArena Math | 1155 | — |
Knowledge Qwen3 14B leads
Qwen1.5-32B: 13.5 (#296), Qwen3 14B: 39.3 (#134)
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 30.7% | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1126 | — |
| MMLU | 74.4% | — |
Multilingual Not comparable
Qwen1.5-32B: 31.4 (#259), Qwen3 14B: —
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1106 | — |
| LMArena Chinese | 1177 | — |
| LMArena French | 1101 | — |
| LMArena German | 1058 | — |
| LMArena Japanese | 1027 | — |
| LMArena Korean | 1008 | — |
| LMArena Russian | 1073 | — |
| LMArena Spanish | 1089 | — |
Instruction Following Not comparable
Qwen1.5-32B: 57.7 (#265), Qwen3 14B: —
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1116 | — |
Long Context Qwen3 14B leads
Qwen1.5-32B: 34.7 (#246), Qwen3 14B: 38.1 (#204)
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1146 | — |
Writing & Preference Not comparable
Qwen1.5-32B: 34.2 (#271), Qwen3 14B: —
| Benchmark | Qwen1.5-32B | Qwen3 14B |
|---|---|---|
| LMArena Text | 1137 | — |
| LMArena Creative Writing | 1083 | — |
| LMArena Multi-Turn | 1140 | — |
Frequently asked questions
Is Qwen1.5-32B better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.5 on the Noometry Index.
Is Qwen1.5-32B or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 31.7 in the Noometry coding category.
How many benchmarks do Qwen1.5-32B and Qwen3 14B share?
1 benchmark has published results for both models. Qwen1.5-32B has 21 scored results on Noometry and Qwen3 14B has 12.