Benchmarks & Performance
Rigorous, reproducible numbers. Gemma 4 31B ranks 3rd globally among open-source models on Arena AI with an ELO of ~1452, beating models 20x its size in practical agentic simulations.
Gemma 4 Family — Internal Comparison
| Benchmark | Gemma 4 31B | Gemma 4 26B | Gemma 3 27B | Improvement |
|---|---|---|---|---|
MMLU Pro Massive Multitask Language Understanding | 85.2% | 82.6% | 67.6% | +26% |
AIME 2026 American Invitational Mathematics Exam | 89.2% | 88.3% | 20.8% | +329% |
LiveCodeBench Live Coding Benchmark v6 | 80% | 77.1% | 29.1% | +175% |
GPQA Diamond Graduate-Level Science QA | 84.3% | 82.3% | 42.4% | +99% |
Tau2 (Agent) Agentic Tool Use Benchmark | 76.9% | 68.2% | 16.2% | +375% |
Visual: Gemma 4 31B vs Gemma 3 27B
Gemma 4 vs Competitors (2026)
How the 31B model compares against the top open model families.
| Metric | Gemma 4 31B | Qwen 3.5 27B | Llama 4 Scout |
|---|---|---|---|
| Reasoning (GPQA) | 84.3% | ~72.0% | 74.3% |
| Mathematics (AIME) | 89.2% | 48.7% | N/A |
| Coding (LCB v6) | 80.0% | 43.0% | N/A |
| Context Window | 256K | 262K | 10M |
| Arena AI ELO | ~1452 | — | — |
| Codeforces ELO | 2150 | — | — |
"—" indicates data not publicly available. Qwen leads in multilingual coverage (201 languages). Llama 4 Scout leads in context length (10M tokens).
Thinking Mode & Deterministic Logic
The 31B model's dominance in mathematics is attributed to its "Thinking Mode," which allows for step-by-step reasoning before outputting a final token. This helps the model avoid "mode collapse" on complex paradoxes or edge cases.
Research variants like Gemma-4-31B-Cognitive-Unshackled demonstrate that by surgically removing "Refusal Vectors" (targeting Layer 39 in the residual stream), developers achieve a 10–15% increase in token generation speed alongside improved performance on complex logical paradoxes.
The intelligence is described as "deterministic and rigorous" — delivering consistent, reproducible answers to complex mathematical and scientific problems that previously required models with 10x the parameter count.
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