Model comparison
Gemma 3 27B vs Qwen3.5-Flash
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 30.8 on the Noometry Index. Gemma 3 27B costs 1.8× less per token, which makes it the better buy when Qwen3.5-Flash's lead doesn't matter for your workload.
Last verified . 24 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 24 benchmarks with published results for both. Gemma 3 27B scores higher in 0 categories and Qwen3.5-Flash in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.5-Flash leads 43.2 to 25.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 22.5% for Gemma 3 27B and 84.4% for Qwen3.5-Flash.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $0.10 / $0.40 for Qwen3.5-Flash.
- Qwen3.5-Flash accepts more context: 1M tokens versus 131K.
- Gemma 3 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 27B | Qwen3.5-Flash | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 30.8 | 42.5 |
| Released | 2025-03-11 | 2026-02-23 |
| Weights | Open | Proprietary |
| Context window | 131K | 1M |
| Max output | 8K | 66K |
| Input $ / M tokens | $0.08 | $0.10 |
| Output $ / M tokens | $0.16 | $0.40 |
| Results tracked | 43 | 32 |
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Category by category
Coding Qwen3.5-Flash leads
Gemma 3 27B: 22.5 (#334), Qwen3.5-Flash: 34.2 (#242)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Coding | 1322 | 1412 |
| Aider Polyglot | 4.9% | — |
| LMArena WebDev | — | 1244 |
| SciCode | 21.2% | — |
| LiveBench Coding | 39.9% | — |
| ALE-Bench | — | 221.8 |
Agentic & Tool Use Not comparable
Gemma 3 27B: 25.1 (#110), Qwen3.5-Flash: —
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | — |
| Vending-Bench 2 | — | 462.69 |
Reasoning Qwen3.5-Flash leads
Gemma 3 27B: 16.7 (#301), Qwen3.5-Flash: 33.7 (#72)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| Chess Puzzles | 0% | 21% |
| LMArena Hard Prompts | 1340 | 1403 |
| DTBench | 52.5% | 82.9% |
| LMCA | 12.3% | 29.1% |
| Epoch Capabilities Index | 130.04 | 143.98 |
| Kagi LLM Benchmark | 40.4% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | 43.8% | — |
| Mystery Game Puzzles | — | 20% |
| LiveBench Data Analysis | 51.5% | — |
| LiveBench | 50% | — |
Math Qwen3.5-Flash leads
Gemma 3 27B: 25.9 (#265), Qwen3.5-Flash: 37.4 (#158)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 22.5% | 84.4% |
| LMArena Math | 1312 | 1407 |
| FrontierMath (Tiers 1-3) | — | 18.2% |
| LiveBench Math | 55.4% | — |
| MATH Level 5 | 74% | — |
| FrontierMath (Feb 2025 set) | — | 6.2% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3.5-Flash leads
Gemma 3 27B: 25.5 (#261), Qwen3.5-Flash: 43.2 (#93)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| GPQA Diamond | 47.7% | 82.3% |
| Vectara Hallucination Rate | 7.4% | 10.5% |
| LMArena Expert | 1304 | 1407 |
| SimpleQA Verified | — | 20.3% |
| Confabulations | 40.3% | — |
Multimodal Not comparable
Gemma 3 27B: 32.6 (#100), Qwen3.5-Flash: —
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Vision | 1164 | — |
| GeoBench | 52% | — |
Multilingual Qwen3.5-Flash leads
Gemma 3 27B: 46.9 (#155), Qwen3.5-Flash: 50.5 (#121)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1334 | 1385 |
| LMArena Chinese | 1346 | 1446 |
| LMArena French | 1368 | 1412 |
| LMArena German | 1362 | 1390 |
| LMArena Japanese | 1287 | 1368 |
| LMArena Korean | 1308 | 1344 |
| LMArena Russian | 1349 | 1379 |
| LMArena Spanish | 1349 | 1400 |
Instruction Following Qwen3.5-Flash leads
Gemma 3 27B: 70.6 (#160), Qwen3.5-Flash: 72.6 (#139)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1321 | 1374 |
| LiveBench Instruction Following | 74.9% | — |
Long Context Qwen3.5-Flash leads
Gemma 3 27B: 27.6 (#293), Qwen3.5-Flash: 42.4 (#124)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1333 | 1392 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference Qwen3.5-Flash leads
Gemma 3 27B: 52.5 (#168), Qwen3.5-Flash: 57.9 (#122)
| Benchmark | Gemma 3 27B | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1358 | 1397 |
| LMArena Creative Writing | 1346 | 1343 |
| LMArena Multi-Turn | 1345 | 1393 |
| Short-Story Creative Writing | 79.9% | — |
| EQ-Bench Creative Writing | 1266 | — |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than Qwen3.5-Flash?
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 30.8 on the Noometry Index. Gemma 3 27B costs 1.8× less per token, which makes it the better buy when Qwen3.5-Flash's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 27B or Qwen3.5-Flash?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; Qwen3.5-Flash lists at $0.10 and $0.40.
Is Gemma 3 27B or Qwen3.5-Flash better for coding?
Qwen3.5-Flash scores higher on coding benchmarks: 34.2 versus 22.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 131K.
How many benchmarks do Gemma 3 27B and Qwen3.5-Flash share?
24 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and Qwen3.5-Flash has 32.