Model comparison
Gemma 2 2b IT vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.0 to 32.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
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Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3 14B leads 39.2 to 29.3.
Side by side
| Gemma 2 2b IT | Qwen3 14B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 32.5 | 35.0 |
| Released | — | 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
Gemma 2 2b IT: 31.8 (#268), Qwen3 14B: 36.7 (#191)
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
| LMArena Coding | 1112 | — |
Agentic & Tool Use Not comparable
Gemma 2 2b IT: —, Qwen3 14B: 29.4 (#78)
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Gemma 2 2b IT leads
Gemma 2 2b IT: 20.5 (#219), Qwen3 14B: 18.1 (#272)
| Benchmark | Gemma 2 2b IT | 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
Gemma 2 2b IT: 30.1 (#212), Qwen3 14B: 37.0 (#102)
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| LMArena Math | 1135 | — |
Knowledge Qwen3 14B leads
Gemma 2 2b IT: 29.3 (#229), Qwen3 14B: 39.2 (#124)
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1096 | — |
Multilingual Not comparable
Gemma 2 2b IT: 32.5 (#252), Qwen3 14B: —
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1121 | — |
| LMArena Chinese | 1132 | — |
| LMArena French | 1156 | — |
| LMArena German | 1114 | — |
| LMArena Japanese | 1083 | — |
| LMArena Korean | 1055 | — |
| LMArena Russian | 1118 | — |
| LMArena Spanish | 1140 | — |
Instruction Following Not comparable
Gemma 2 2b IT: 58.1 (#258), Qwen3 14B: —
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1118 | — |
Long Context Qwen3 14B leads
Gemma 2 2b IT: 34.2 (#245), Qwen3 14B: 38.0 (#201)
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1130 | — |
Writing & Preference Not comparable
Gemma 2 2b IT: 36.6 (#258), Qwen3 14B: —
| Benchmark | Gemma 2 2b IT | Qwen3 14B |
|---|---|---|
| LMArena Text | 1156 | — |
| LMArena Creative Writing | 1147 | — |
| LMArena Multi-Turn | 1118 | — |
Frequently asked questions
Is Gemma 2 2b IT better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.0 to 32.5 on the Noometry Index.
Is Gemma 2 2b IT or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 36.7 versus 31.8 in the Noometry coding category.
How many benchmarks do Gemma 2 2b IT and Qwen3 14B share?
0 benchmarks have published results for both models. Gemma 2 2b IT has 17 scored results on Noometry and Qwen3 14B has 12.