Gemma 4 E4b Model Size

https://ai.google.dev › gemma › docs › core
The models are available in five distinct sizes E2B E4B 12B 26B A4B and 31B Their diverse sizes make them deployable in environments ranging from high end phones to laptops and

https://huggingface.co › google
Gemma 4 models are designed to deliver frontier level performance at each size targeting deployment scenarios from mobile and edge devices E2B E4B to consumer GPUs and workstations 26B A4B

https://gemma4.dev › models
Unlike larger Gemma 4 variants that require datacenter GPUs Gemma 4 E4B runs comfortably on any modern consumer GPU with 8GB VRAM making it the most practical Gemma 4 model for everyday

https://ollama.com › library
Optimized for On Device Smaller models are specifically designed for efficient local execution on laptops and mobile devices Increased Context Window The small models feature a 128K context

https://developers.google.com › edge › litert-lm › models
Gemma 4 models are designed to deliver frontier level performance at each size targeting deployment scenarios from mobile and edge devices E2B E4B to consumer GPUs and workstations

https://deepmind.google › models › gemma
These models were evaluated against a large collection of datasets and metrics to cover different aspects of text generation See additional benchmarks in model card

https://aurigait.com › blog
Gemma 4 is Google DeepMind s most capable open AI model family released April 2026 under Apache 2 0 This guide covers all 4 model sizes E2B E4B 26B MoE 31B Dense

https://theairankings.com › google
Gemma 4 models are multimodal text and image input with text output and audio input on the E2B E4B and 12B sizes with a 256K token context window and multilingual coverage

https://codersera.com › blog
Gemma 4 is the most consequential open weight model release of the year so far and not just because of the benchmarks Google shipped four model sizes native multimodality a 256K