Google Gemma 4: How a 31B Model Beats 600B+ Giants (Benchmarks + NVIDIA Co-Optimization)

Google Gemma 4: How a 31B Model Beats 600B+ Giants Google DeepMind released Gemma 4 on April 2, 2026 — and the benchmarks demand attention. A 31B parameter model ranking #3 on Arena AI's open model leaderboard , beating models 20x its size. Let's break it down. The Lineup: 4 Models for Every Scale Model Parameters Target Hardware Context Window E2B 2B (effective) Smartphone, Raspberry Pi, Jetson Nano 128K E4B 4B (effective) Mobile, Edge devices 128K 26B MoE 26B (128 experts, 3.8B active) Consumer GPU, Workstations 256K 31B Dense 31B H100, RTX 4090, Cloud 256K The E2B model runs on a $35 Raspberry Pi . The 31B Dense model runs on a single RTX 4090 (24GB VRAM). That's the range we're talking about. Benchmark Shock: One Generation, Massive Leap Benchmark Gemma 4 31B Gemma 3 Delta AIME 2026 Math 89.2% 20.8% +68.4pt LiveCodeBench v6 80.0% 29.1% +50.9pt GPQA Diamond Science 84.3% 42.4% +41.9pt τ2-bench Agent 76.9% 16.2% +60.7pt Codeforces Elo 2150 110 +2040 A Codeforces Elo of 2150 is Candid