Model comparison
Gemma 3n E4b IT vs Qwen3-30B-A3B
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 37.3 on the Noometry Index.
Last verified . 18 shared benchmarks.
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Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. Gemma 3n E4b IT scores higher in 1 category and Qwen3-30B-A3B in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemma 3n E4b IT leads 38.7 to 31.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 31.5% for Gemma 3n E4b IT and 54.9% for Qwen3-30B-A3B.
Side by side
| Gemma 3n E4b IT | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 37.3 | 38.9 |
| Released | — | 2025-04-28 |
| Weights | Open | Open |
| Context window | — | 41K |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.12 |
| Output $ / M tokens | — | $0.50 |
| Results tracked | 18 | 32 |
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Category by category
Coding Too close to call
Gemma 3n E4b IT: 37.0 (#198), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| LMArena Coding | 1268 | 1416 |
| SciCode | — | 33.3% |
| WeirdML | — | 29.8% |
Agentic & Tool Use Not comparable
Gemma 3n E4b IT: —, Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
Reasoning Qwen3-30B-A3B leads
Gemma 3n E4b IT: 19.9 (#247), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| Kagi LLM Benchmark | 31.5% | 54.9% |
| LMArena Hard Prompts | 1284 | 1398 |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 8% |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |
| Epoch Capabilities Index | — | 139.63 |
Math Qwen3-30B-A3B leads
Gemma 3n E4b IT: 35.1 (#188), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| LMArena Math | 1251 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
| OTIS Mock AIME 2024-2025 | — | 70.3% |
Knowledge Qwen3-30B-A3B leads
Gemma 3n E4b IT: 34.2 (#198), Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| LMArena Expert | 1246 | 1396 |
| GPQA Diamond | — | 70.1% |
| Confabulations | — | 12.3% |
Multilingual Qwen3-30B-A3B leads
Gemma 3n E4b IT: 43.4 (#183), Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1285 | 1372 |
| LMArena Chinese | 1309 | 1433 |
| LMArena French | 1330 | 1418 |
| LMArena German | 1311 | 1380 |
| LMArena Japanese | 1272 | 1337 |
| LMArena Korean | 1259 | 1331 |
| LMArena Russian | 1288 | 1370 |
| LMArena Spanish | 1305 | 1404 |
Instruction Following Qwen3-30B-A3B leads
Gemma 3n E4b IT: 66.1 (#210), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1255 | 1363 |
Long Context Gemma 3n E4b IT leads
Gemma 3n E4b IT: 38.7 (#191), Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1276 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Qwen3-30B-A3B leads
Gemma 3n E4b IT: 50.1 (#186), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | Gemma 3n E4b IT | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1306 | 1384 |
| LMArena Creative Writing | 1287 | 1317 |
| LMArena Multi-Turn | 1276 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
Frequently asked questions
Is Gemma 3n E4b IT better than Qwen3-30B-A3B?
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 37.3 on the Noometry Index.
Is Gemma 3n E4b IT or Qwen3-30B-A3B better for coding?
They score almost the same on coding (37.0 vs 37.5); test both on your own repository before choosing.
How many benchmarks do Gemma 3n E4b IT and Qwen3-30B-A3B share?
18 benchmarks have published results for both models. Gemma 3n E4b IT has 18 scored results on Noometry and Qwen3-30B-A3B has 32.