Gemma 4 31BvsQwen3.5-27B
Across 4 shared benchmarks, Qwen3.5-27B leads overall: Gemma 4 31B wins 1, Qwen3.5-27B wins 3, with 0 ties and an average score difference of +61.70.
Gemma 4 31B
DeepMind · 2026-04-02 · Chat model
Qwen3.5-27B
阿里巴巴 · 2026-02-25 · Reasoning model
Gemma 4 31B1 win(25%)(75%)3 winsQwen3.5-27B
Benchmark scores
Grouped by capability, sorted by largest gap within each. 4 shared benchmarks.
Agent Level Benchmark
Qwen3.5-27B 1/1| Benchmark | Gemma 4 31B | Qwen3.5-27B | Diff |
|---|---|---|---|
| τ²-Bench | 76.9020 / 44Thinking (With Tools) | 7917 / 44Thinking (With Tools) | -2.10 |
Coding and Software Engineer
Gemma 4 31B 1/1| Benchmark | Gemma 4 31B | Qwen3.5-27B | Diff |
|---|---|---|---|
| CodeForces | 2,15014 / 21Thinking (No Tools) | 1,89917 / 21Thinking (No Tools) | +251 |
General Evaluation
Qwen3.5-27B 1/1| Benchmark | Gemma 4 31B | Qwen3.5-27B | Diff |
|---|---|---|---|
| GPQA Diamond | 84.30110 / 274Thinking (No Tools) | 85.5098 / 274Thinking (No Tools) | -1.20 |
General Knowledge
Qwen3.5-27B 1/1| Benchmark | Gemma 4 31B | Qwen3.5-27B | Diff |
|---|---|---|---|
| MMLU Pro | 85.2025 / 134Thinking (No Tools) | 86.1020 / 134Thinking (No Tools) | -0.90 |
Specs
| Field | Gemma 4 31B | Qwen3.5-27B |
|---|---|---|
| Publisher | DeepMind | 阿里巴巴 |
| Release date | 2026-04-02 | 2026-02-25 |
| Model type | Chat model | Reasoning model |
| Architecture | Dense | Dense |
| Parameters | 30.7B | 27B |
| Context length | 256K | 1010K |
| Max output | 32K | 248320 |
Summary
- Gemma 4 31Bleads in:Coding and Software Engineer (1/1)
- Qwen3.5-27Bleads in:Agent Level Benchmark (1/1), General Evaluation (1/1), General Knowledge (1/1)
On average across the 4 shared benchmarks, Gemma 4 31B scores 61.70 higher.
Largest single-benchmark gap: CodeForces — Gemma 4 31B 2,150 vs Qwen3.5-27B 1,899 (+251).
Page generated from structured model, pricing and benchmark records. No real-time LLM is used to write the prose.