Gemma 4: From Raspberry Pi to Research Workstation — One Architecture, No Quality Compromise
Gemma 4 is a family of four open-weights multimodal models released by Google DeepMind on April 2, 2026, under the Apache 2.0 license, designed to operate efficiently across devices from Raspberry Pi to research workstations. The models leverage architectural innovations such as Per-Layer Embeddings and hybrid local-global attention to maintain high performance without compromising quality. These advancements enable strong benchmark results, including a 2B-parameter model achieving 37.5% on AIME 2026 within 1.5 GB of RAM.
- ▪Gemma 4 includes four models: E2B, E4B, 26B, and 31B, all released under the Apache 2.0 license.
- ▪The E2B model achieves 37.5% accuracy on the AIME 2026 math benchmark while running on 1.5 GB of quantized memory.
- ▪Per-Layer Embeddings (PLE) allow smaller models to maintain high performance by using dedicated, low-dimensional embedding tables per layer.
- ▪Hybrid attention combines local sliding-window and global full-context attention to support up to 256K context efficiently.
- ▪The 31B dense model is designed for maximum accuracy and fine-tuning, scoring 89.2% on AIME 2026.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3813172) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Prakhar Shukla Posted on May 17 Gemma 4: From Raspberry Pi to Research Workstation — One Architecture, No Quality Compromise #devchallenge #gemmachallenge #gemma Gemma 4 Challenge: Write about Gemma 4 Submission This is a submission for the Gemma 4 Challenge: Write About Gemma 4 TL;DR — Gemma 4 is four open-weights multimodal models (E2B, E4B, 26B, 31B) under Apache 2.0, released April 2, 2026.
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