Model comparison
Gemini 2.0 Flash (Feb 2025) vs Qwen3.5 27B
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 35.1 on the Noometry Index.
Last verified . 20 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 20 benchmarks with published results for both. Gemini 2.0 Flash (Feb 2025) scores higher in 1 category and Qwen3.5 27B in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5 27B leads 27.5 to 15.2.
- The biggest single-benchmark swing is DTBench: 63.2% for Gemini 2.0 Flash (Feb 2025) and 82.4% for Qwen3.5 27B.
- Qwen3.5 27B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 35.1 | 41.9 |
| Released | 2024-12-06 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.30 |
| Output $ / M tokens | — | $2.40 |
| Results tracked | 54 | 28 |
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Category by category
Coding Qwen3.5 27B leads
Gemini 2.0 Flash (Feb 2025): 28.4 (#315), Qwen3.5 27B: 38.9 (#168)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| WeirdML | 25.8% | 39.5% |
| LMArena Coding | 1350 | 1427 |
| SWE-bench Verified (bash only) | 13.5% | — |
| Aider Polyglot | 38.2% | — |
| LMArena WebDev | — | 1358 |
| BigCodeBench Instruct | 45.9% | — |
| LiveBench Coding | 63.4% | — |
| BigCodeBench Complete | 59.9% | — |
| CadEval | 30% | — |
| ALE-Bench | — | 349.45 |
Agentic & Tool Use Not comparable
Gemini 2.0 Flash (Feb 2025): 28.1 (#92), Qwen3.5 27B: —
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| TheAgentCompany | 11.4% | — |
| Vending-Bench 2 | — | 201.98 |
Reasoning Qwen3.5 27B leads
Gemini 2.0 Flash (Feb 2025): 15.2 (#318), Qwen3.5 27B: 27.5 (#117)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1346 | 1414 |
| DTBench | 63.2% | 82.4% |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 31.1% | — |
| Kagi LLM Benchmark | 37.8% | — |
| NYT Connections (extended) | — | 47.9% |
| EnigmaEval | 1.1% | — |
| Thematic Generalization | — | 45.5% |
| LiveBench Reasoning | 78.2% | — |
| LiveBench Data Analysis | 69.4% | — |
| LMCA | — | 34% |
| Epoch Capabilities Index | 135.36 | — |
| LiveBench | 66.9% | — |
Math Too close to call
Gemini 2.0 Flash (Feb 2025): 37.9 (#146), Qwen3.5 27B: 38.8 (#127)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1352 | 1429 |
| MathArena Final-Answer Competitions | — | 56.7% |
| OTIS Mock AIME 2024-2025 | 57.8% | — |
| Omni-MATH | 45.9% | — |
| LiveBench Math | 75.8% | — |
| MATH Level 5 | 82.2% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |
Knowledge Qwen3.5 27B leads
Gemini 2.0 Flash (Feb 2025): 32.0 (#213), Qwen3.5 27B: 38.0 (#150)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Expert | 1339 | 1428 |
| GPQA Diamond | 64.1% | — |
| Humanity's Last Exam | 6.6% | — |
| MMLU-Pro | 73.7% | — |
| Confabulations | 12.4% | — |
| Vectara Hallucination Rate | — | 12.1% |
| GPQA (HELM) | 55.6% | — |
| MMLU | 79.7% | — |
Multimodal Qwen3.5 27B leads
Gemini 2.0 Flash (Feb 2025): 36.5 (#79), Qwen3.5 27B: 39.4 (#59)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | 1158 | 1241 |
| GeoBench | 77% | — |
Multilingual Qwen3.5 27B leads
Gemini 2.0 Flash (Feb 2025): 47.4 (#149), Qwen3.5 27B: 50.8 (#115)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 1342 | 1390 |
| LMArena Chinese | 1373 | 1478 |
| LMArena French | 1391 | 1410 |
| LMArena German | 1353 | 1393 |
| LMArena Japanese | 1294 | 1345 |
| LMArena Korean | 1313 | 1358 |
| LMArena Russian | 1351 | 1390 |
| LMArena Spanish | 1363 | 1407 |
Instruction Following Too close to call
Gemini 2.0 Flash (Feb 2025): 74.4 (#97), Qwen3.5 27B: 73.5 (#119)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1336 | 1393 |
| LiveBench Instruction Following | 85.8% | — |
| IFEval | 84.1% | — |
Long Context Qwen3.5 27B leads
Gemini 2.0 Flash (Feb 2025): 38.1 (#203), Qwen3.5 27B: 43.1 (#106)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 1344 | 1413 |
| Fiction.LiveBench | 61.1% | — |
Writing & Preference Qwen3.5 27B leads
Gemini 2.0 Flash (Feb 2025): 49.5 (#190), Qwen3.5 27B: 59.3 (#111)
| Benchmark | Gemini 2.0 Flash (Feb 2025) | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1354 | 1409 |
| LMArena Creative Writing | 1340 | 1362 |
| LMArena Multi-Turn | 1350 | 1410 |
| Short-Story Creative Writing | 73.8% | — |
| EQ-Bench Creative Writing | 1128 | — |
| WildBench | 80% | — |
| LiveBench Language | 51.3% | — |
Frequently asked questions
Is Gemini 2.0 Flash (Feb 2025) better than Qwen3.5 27B?
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 35.1 on the Noometry Index.
Is Gemini 2.0 Flash (Feb 2025) or Qwen3.5 27B better for coding?
Qwen3.5 27B scores higher on coding benchmarks: 38.9 versus 28.4 in the Noometry coding category.
How many benchmarks do Gemini 2.0 Flash (Feb 2025) and Qwen3.5 27B share?
20 benchmarks have published results for both models. Gemini 2.0 Flash (Feb 2025) has 54 scored results on Noometry and Qwen3.5 27B has 28.