Model comparison
Gemini 2.5 Flash vs Qwen3.5 27B
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 39.3 on the Noometry Index.
Last verified . 24 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 24 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 5 categories and Qwen3.5 27B in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5 27B leads 27.5 to 18.1.
- The biggest single-benchmark swing is LMCA: 27.5% for Gemini 2.5 Flash and 34% for Qwen3.5 27B.
- Both cost about the same: $0.30 input and $2.50 output per million tokens.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 262K.
- Qwen3.5 27B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash | Qwen3.5 27B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 39.3 | 41.9 |
| Released | 2025-04-17 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.30 | $0.30 |
| Output $ / M tokens | $2.50 | $2.40 |
| Results tracked | 54 | 28 |
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Category by category
Coding Qwen3.5 27B leads
Gemini 2.5 Flash: 35.8 (#220), Qwen3.5 27B: 38.9 (#168)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| WeirdML | 41.9% | 39.5% |
| LMArena Coding | 1424 | 1427 |
| ALE-Bench | 661.88 | 349.45 |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1358 |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash: 30.8 (#74), Qwen3.5 27B: —
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| Vending-Bench 2 | 548.84 | 201.98 |
| Terminal-Bench | 17.1% | — |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
Reasoning Qwen3.5 27B leads
Gemini 2.5 Flash: 18.1 (#286), Qwen3.5 27B: 27.5 (#117)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1422 | 1414 |
| DTBench | 76.5% | 82.4% |
| LMCA | 27.5% | 34% |
| ARC-AGI-2 | 2.5% | — |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| NYT Connections (extended) | — | 47.9% |
| ARC-AGI-1 | 33.3% | — |
| CritPt | 1.1% | — |
| EnigmaEval | 2.7% | — |
| Thematic Generalization | — | 45.5% |
| Epoch Capabilities Index | 143.03 | — |
| ForecastBench | 60.6 | — |
Math Gemini 2.5 Flash leads
Gemini 2.5 Flash: 39.9 (#98), Qwen3.5 27B: 38.8 (#127)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1415 | 1429 |
| MathArena Final-Answer Competitions | — | 56.7% |
| OTIS Mock AIME 2024-2025 | 73.1% | — |
| Omni-MATH | 38.5% | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Qwen3.5 27B leads
Gemini 2.5 Flash: 36.4 (#168), Qwen3.5 27B: 38.0 (#150)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| Vectara Hallucination Rate | 7.8% | 12.1% |
| LMArena Expert | 1426 | 1428 |
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| Confabulations | 16.8% | — |
| GPQA (HELM) | 39% | — |
Multimodal Gemini 2.5 Flash leads
Gemini 2.5 Flash: 41.8 (#32), Qwen3.5 27B: 39.4 (#59)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | 1253 | 1241 |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |
Multilingual Gemini 2.5 Flash leads
Gemini 2.5 Flash: 52.3 (#88), Qwen3.5 27B: 50.8 (#115)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 1409 | 1390 |
| LMArena Chinese | 1450 | 1478 |
| LMArena French | 1433 | 1410 |
| LMArena German | 1418 | 1393 |
| LMArena Japanese | 1405 | 1345 |
| LMArena Korean | 1385 | 1358 |
| LMArena Russian | 1415 | 1390 |
| LMArena Spanish | 1421 | 1407 |
Instruction Following Gemini 2.5 Flash leads
Gemini 2.5 Flash: 75.7 (#54), Qwen3.5 27B: 73.5 (#119)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1405 | 1393 |
| IFEval | 89.8% | — |
Long Context Gemini 2.5 Flash leads
Gemini 2.5 Flash: 47.5 (#17), Qwen3.5 27B: 43.1 (#106)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 1419 | 1413 |
| Fiction.LiveBench | 77.8% | — |
Writing & Preference Qwen3.5 27B leads
Gemini 2.5 Flash: 53.8 (#157), Qwen3.5 27B: 59.3 (#111)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1417 | 1409 |
| LMArena Creative Writing | 1400 | 1362 |
| LMArena Multi-Turn | 1408 | 1410 |
| Short-Story Creative Writing | 76.5% | — |
| EQ-Bench Creative Writing | 1137 | — |
| WildBench | 81.7% | — |
Frequently asked questions
Is Gemini 2.5 Flash better than Qwen3.5 27B?
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 39.3 on the Noometry Index.
Which is cheaper, Gemini 2.5 Flash or Qwen3.5 27B?
Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; Gemini 2.5 Flash lists at $0.30 and $2.50.
Is Gemini 2.5 Flash or Qwen3.5 27B better for coding?
Qwen3.5 27B scores higher on coding benchmarks: 38.9 versus 35.8 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Flash and Qwen3.5 27B share?
24 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Qwen3.5 27B has 28.