Model comparison
Gemini 3 Pro vs Qwen3-30B-A3B
Gemini 3 Pro is the stronger model overall, scoring 54.8 to 38.9 on the Noometry Index.
Last verified . 26 shared benchmarks.
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Alibaba (Qwen)Summary
- They share 26 benchmarks with published results for both. Gemini 3 Pro scores higher in 9 categories and Qwen3-30B-A3B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3 Pro leads 52.5 to 22.2.
- The biggest single-benchmark swing is WeirdML: 69.9% for Gemini 3 Pro and 29.8% for Qwen3-30B-A3B.
- Qwen3-30B-A3B has downloadable open weights; the other is API-only.
Side by side
| Gemini 3 Pro | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 54.8 | 38.9 |
| Released | 2025-11-18 | 2025-04-28 |
| Weights | Proprietary | Open |
| Context window | — | 41K |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.12 |
| Output $ / M tokens | — | $0.50 |
| Results tracked | 67 | 32 |
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Category by category
Coding Gemini 3 Pro leads
Gemini 3 Pro: 51.6 (#39), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| WeirdML | 69.9% | 29.8% |
| LMArena Coding | 1481 | 1416 |
| SWE-bench Verified | 72.9% | — |
| SWE-bench Verified (bash only) | 74.2% | — |
| LMArena WebDev | 1440 | — |
| SWE-bench Multilingual | 68.7% | — |
| SciCode | — | 33.3% |
| GSO | 18.6% | — |
| ALE-Bench | 1,177 | — |
| AlgoTune | 1.83 | — |
Agentic & Tool Use Gemini 3 Pro leads
Gemini 3 Pro: 40.6 (#23), Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 72.5% | 41.4% |
| Terminal-Bench | 69.4% | — |
| GDPval | 40.3% | — |
| Remote Labor Index | 1.3% | — |
| τ²-bench Airline | 80.5% | — |
| τ²-bench Banking | 18% | — |
| τ²-bench Retail | 75.9% | — |
| τ²-bench Telecom | 91% | — |
| DeepResearch Bench | 46.3% | — |
| BALROG | 58.1% | — |
| LMArena Search | 1207 | — |
| METR Time Horizons | 71% | — |
| Vending-Bench 2 | 5,478 | — |
Reasoning Gemini 3 Pro leads
Gemini 3 Pro: 52.5 (#31), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| Kagi LLM Benchmark | 80.1% | 54.9% |
| CritPt | 6.9% | 0.3% |
| Chess Puzzles | 31% | 8% |
| LMArena Hard Prompts | 1480 | 1398 |
| Epoch Capabilities Index | 152.92 | 139.63 |
| ARC-AGI-2 | 31.1% | — |
| SimpleBench | 76.4% | — |
| NYT Connections (extended) | 94.4% | — |
| ARC-AGI-1 | 75% | — |
| EnigmaEval | 18.2% | — |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |
| ForecastBench | 61.2 | — |
Math Gemini 3 Pro leads
Gemini 3 Pro: 49.9 (#59), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| MathArena Final-Answer Competitions | 67% | 47.8% |
| OTIS Mock AIME 2024-2025 | 91.4% | 70.3% |
| LMArena Math | 1476 | 1394 |
| ProofBench | 20% | — |
| Omni-MATH | 55.5% | — |
| FrontierMath (Feb 2025 set) | 37.6% | — |
| FrontierMath Tier 4 (v1) | 18.8% | — |
Knowledge Gemini 3 Pro leads
Gemini 3 Pro: 64.4 (#16), Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 92.6% | 70.1% |
| LMArena Expert | 1475 | 1396 |
| Humanity's Last Exam | 37.5% | — |
| MMLU-Pro | 90.3% | — |
| Confabulations | — | 12.3% |
| Vectara Hallucination Rate | 13.6% | — |
| GPQA (HELM) | 80.3% | — |
Multimodal Not comparable
Gemini 3 Pro: 57.6 (#2), Qwen3-30B-A3B: —
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Vision | 1305 | — |
| GeoBench | 84% | — |
| VPCT | 91% | — |
| LMArena Document | 1434 | — |
Multilingual Gemini 3 Pro leads
Gemini 3 Pro: 56.9 (#16), Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1474 | 1372 |
| LMArena Chinese | 1523 | 1433 |
| LMArena French | 1492 | 1418 |
| LMArena German | 1515 | 1380 |
| LMArena Japanese | 1510 | 1337 |
| LMArena Korean | 1448 | 1331 |
| LMArena Russian | 1493 | 1370 |
| LMArena Spanish | 1470 | 1404 |
Instruction Following Gemini 3 Pro leads
Gemini 3 Pro: 76.3 (#45), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1458 | 1363 |
| IFEval | 87.7% | — |
Long Context Gemini 3 Pro leads
Gemini 3 Pro: 44.0 (#79), Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1471 | 1379 |
| Fiction.LiveBench | — | 40.6% |
| CL-bench | 15.8% | — |
Writing & Preference Gemini 3 Pro leads
Gemini 3 Pro: 66.4 (#35), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | Gemini 3 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1479 | 1384 |
| LMArena Creative Writing | 1482 | 1317 |
| LMArena Multi-Turn | 1484 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench Creative Writing | 1525 | — |
| WildBench | 85.9% | — |
Frequently asked questions
Is Gemini 3 Pro better than Qwen3-30B-A3B?
Gemini 3 Pro is the stronger model overall, scoring 54.8 to 38.9 on the Noometry Index.
Is Gemini 3 Pro or Qwen3-30B-A3B better for coding?
Gemini 3 Pro scores higher on coding benchmarks: 51.6 versus 37.5 in the Noometry coding category.
How many benchmarks do Gemini 3 Pro and Qwen3-30B-A3B share?
26 benchmarks have published results for both models. Gemini 3 Pro has 67 scored results on Noometry and Qwen3-30B-A3B has 32.