Model comparison
Gemma 3 27B vs Qwen3.5 397B-A17B
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 30.8 on the Noometry Index. Gemma 3 27B costs 14× less per token, which makes it the better buy when Qwen3.5 397B-A17B's lead doesn't matter for your workload.
Last verified . 26 shared benchmarks.
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Alibaba (Qwen)Summary
- They share 26 benchmarks with published results for both. Gemma 3 27B scores higher in 0 categories and Qwen3.5 397B-A17B in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.5 397B-A17B leads 53.3 to 25.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 22.5% for Gemma 3 27B and 88.9% for Qwen3.5 397B-A17B.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $0.60 / $3.60 for Qwen3.5 397B-A17B.
- Qwen3.5 397B-A17B accepts more context: 262K tokens versus 131K.
Side by side
| Gemma 3 27B | Qwen3.5 397B-A17B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 30.8 | 46.0 |
| Released | 2025-03-11 | 2026-02-01 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 8K | 66K |
| Input $ / M tokens | $0.08 | $0.60 |
| Output $ / M tokens | $0.16 | $3.60 |
| Results tracked | 43 | 36 |
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Category by category
Coding Qwen3.5 397B-A17B leads
Gemma 3 27B: 22.5 (#334), Qwen3.5 397B-A17B: 42.0 (#114)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Coding | 1322 | 1465 |
| Aider Polyglot | 4.9% | — |
| LMArena WebDev | — | 1400 |
| SciCode | 21.2% | — |
| LiveBench Coding | 39.9% | — |
Agentic & Tool Use Qwen3.5 397B-A17B leads
Gemma 3 27B: 25.1 (#110), Qwen3.5 397B-A17B: 33.3 (#53)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| APEX-Agents | — | 24.9% |
| Berkeley Function Calling Leaderboard | 29.5% | — |
| τ²-bench Airline | — | 81.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 84.4% |
| τ²-bench Telecom | — | 97.8% |
Reasoning Qwen3.5 397B-A17B leads
Gemma 3 27B: 16.7 (#301), Qwen3.5 397B-A17B: 34.5 (#70)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| Kagi LLM Benchmark | 40.4% | 73.7% |
| Chess Puzzles | 0% | 13% |
| LMArena Hard Prompts | 1340 | 1448 |
| DTBench | 52.5% | 87.5% |
| LMCA | 12.3% | 37.9% |
| Epoch Capabilities Index | 130.04 | 146.65 |
| NYT Connections (extended) | — | 58.9% |
| CritPt | 0% | — |
| Thematic Generalization | — | 65.1% |
| LiveBench Reasoning | 43.8% | — |
| Mystery Game Puzzles | — | 18% |
| LiveBench Data Analysis | 51.5% | — |
| LiveBench | 50% | — |
Math Qwen3.5 397B-A17B leads
Gemma 3 27B: 25.9 (#265), Qwen3.5 397B-A17B: 46.1 (#73)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 22.5% | 88.9% |
| LMArena Math | 1312 | 1454 |
| FrontierMath (Tiers 1-3) | — | 31.2% |
| LiveBench Math | 55.4% | — |
| MATH Level 5 | 74% | — |
Knowledge Qwen3.5 397B-A17B leads
Gemma 3 27B: 25.5 (#261), Qwen3.5 397B-A17B: 53.3 (#58)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| GPQA Diamond | 47.7% | 86.4% |
| LMArena Expert | 1304 | 1462 |
| Confabulations | 40.3% | — |
| Vectara Hallucination Rate | 7.4% | — |
Multimodal Qwen3.5 397B-A17B leads
Gemma 3 27B: 32.6 (#100), Qwen3.5 397B-A17B: 40.7 (#44)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Vision | 1164 | 1263 |
| GeoBench | 52% | — |
Multilingual Qwen3.5 397B-A17B leads
Gemma 3 27B: 46.9 (#155), Qwen3.5 397B-A17B: 53.7 (#59)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Non-English | 1334 | 1430 |
| LMArena Chinese | 1346 | 1500 |
| LMArena French | 1368 | 1461 |
| LMArena German | 1362 | 1447 |
| LMArena Japanese | 1287 | 1426 |
| LMArena Korean | 1308 | 1384 |
| LMArena Russian | 1349 | 1429 |
| LMArena Spanish | 1349 | 1441 |
Instruction Following Qwen3.5 397B-A17B leads
Gemma 3 27B: 70.6 (#160), Qwen3.5 397B-A17B: 75.0 (#77)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Instruction Following | 1321 | 1424 |
| LiveBench Instruction Following | 74.9% | — |
Long Context Qwen3.5 397B-A17B leads
Gemma 3 27B: 27.6 (#293), Qwen3.5 397B-A17B: 44.1 (#74)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Longer Query | 1333 | 1442 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference Qwen3.5 397B-A17B leads
Gemma 3 27B: 52.5 (#168), Qwen3.5 397B-A17B: 62.3 (#79)
| Benchmark | Gemma 3 27B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Text | 1358 | 1438 |
| LMArena Creative Writing | 1346 | 1401 |
| EQ-Bench Creative Writing | 1266 | 1478 |
| LMArena Multi-Turn | 1345 | 1446 |
| Short-Story Creative Writing | 79.9% | — |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than Qwen3.5 397B-A17B?
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 30.8 on the Noometry Index. Gemma 3 27B costs 14× less per token, which makes it the better buy when Qwen3.5 397B-A17B's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 27B or Qwen3.5 397B-A17B?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; Qwen3.5 397B-A17B lists at $0.60 and $3.60.
Is Gemma 3 27B or Qwen3.5 397B-A17B better for coding?
Qwen3.5 397B-A17B scores higher on coding benchmarks: 42.0 versus 22.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5 397B-A17B does, with 262K tokens against 131K.
How many benchmarks do Gemma 3 27B and Qwen3.5 397B-A17B share?
26 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and Qwen3.5 397B-A17B has 36.