Model comparison
Gemma 2 27B vs Qwen3.5-Flash
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 29.4 on the Noometry Index.
Last verified . 22 shared benchmarks.
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Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. Gemma 2 27B scores higher in 0 categories and Qwen3.5-Flash in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.5-Flash leads 37.4 to 10.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.4% for Gemma 2 27B and 84.4% for Qwen3.5-Flash.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.65 / $0.65 for Gemma 2 27B.
- Qwen3.5-Flash accepts more context: 1M tokens versus 8K.
- Gemma 2 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 2 27B | Qwen3.5-Flash | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 29.4 | 42.5 |
| Released | 2024-06-24 | 2026-02-23 |
| Weights | Open | Proprietary |
| Context window | 8K | 1M |
| Max output | 2K | 66K |
| Input $ / M tokens | $0.65 | $0.10 |
| Output $ / M tokens | $0.65 | $0.40 |
| Results tracked | 34 | 32 |
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Category by category
Coding Too close to call
Gemma 2 27B: 34.1 (#246), Qwen3.5-Flash: 34.2 (#242)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Coding | 1211 | 1412 |
| LMArena WebDev | — | 1244 |
| BigCodeBench Instruct | 42.8% | — |
| LiveBench Coding | 36% | — |
| BigCodeBench Complete | 52.5% | — |
| ALE-Bench | — | 221.8 |
Agentic & Tool Use Not comparable
Gemma 2 27B: —, Qwen3.5-Flash: —
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| Vending-Bench 2 | — | 462.69 |
Reasoning Qwen3.5-Flash leads
Gemma 2 27B: 15.3 (#315), Qwen3.5-Flash: 33.7 (#72)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Hard Prompts | 1198 | 1403 |
| DTBench | 48% | 82.9% |
| LMCA | 7.1% | 29.1% |
| Epoch Capabilities Index | 122.08 | 143.98 |
| Chess Puzzles | — | 21% |
| LiveBench Reasoning | 28.1% | — |
| Mystery Game Puzzles | — | 20% |
| LiveBench Data Analysis | 47.9% | — |
| LiveBench | 38.2% | — |
Math Qwen3.5-Flash leads
Gemma 2 27B: 10.7 (#311), Qwen3.5-Flash: 37.4 (#158)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.4% | 84.4% |
| LMArena Math | 1212 | 1407 |
| FrontierMath (Tiers 1-3) | — | 18.2% |
| LiveBench Math | 26.5% | — |
| MATH Level 5 | 27.9% | — |
| FrontierMath (Feb 2025 set) | — | 6.2% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3.5-Flash leads
Gemma 2 27B: 19.0 (#280), Qwen3.5-Flash: 43.2 (#93)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| GPQA Diamond | 36.5% | 82.3% |
| LMArena Expert | 1172 | 1407 |
| SimpleQA Verified | — | 20.3% |
| Confabulations | 27.1% | — |
| Vectara Hallucination Rate | — | 10.5% |
| MMLU | 75.7% | — |
Multilingual Qwen3.5-Flash leads
Gemma 2 27B: 38.6 (#226), Qwen3.5-Flash: 50.5 (#121)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1217 | 1385 |
| LMArena Chinese | 1221 | 1446 |
| LMArena French | 1247 | 1412 |
| LMArena German | 1209 | 1390 |
| LMArena Japanese | 1175 | 1368 |
| LMArena Korean | 1174 | 1344 |
| LMArena Russian | 1234 | 1379 |
| LMArena Spanish | 1228 | 1400 |
Instruction Following Qwen3.5-Flash leads
Gemma 2 27B: 60.5 (#249), Qwen3.5-Flash: 72.6 (#139)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1206 | 1374 |
| LiveBench Instruction Following | 58.1% | — |
Long Context Qwen3.5-Flash leads
Gemma 2 27B: 37.3 (#218), Qwen3.5-Flash: 42.4 (#124)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1231 | 1392 |
Writing & Preference Qwen3.5-Flash leads
Gemma 2 27B: 44.2 (#225), Qwen3.5-Flash: 57.9 (#122)
| Benchmark | Gemma 2 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1231 | 1397 |
| LMArena Creative Writing | 1241 | 1343 |
| LMArena Multi-Turn | 1224 | 1393 |
| LiveBench Language | 32.6% | — |
Frequently asked questions
Is Gemma 2 27B better than Qwen3.5-Flash?
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 29.4 on the Noometry Index.
Which is cheaper, Gemma 2 27B or Qwen3.5-Flash?
Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Gemma 2 27B lists at $0.65 and $0.65.
Is Gemma 2 27B or Qwen3.5-Flash better for coding?
They score almost the same on coding (34.1 vs 34.2); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 8K.
How many benchmarks do Gemma 2 27B and Qwen3.5-Flash share?
22 benchmarks have published results for both models. Gemma 2 27B has 34 scored results on Noometry and Qwen3.5-Flash has 32.