Google has launched its new on-device AI model Gemma 3n, which was first announced in May 2025. This model can perform audio, image, video, and text processing without an internet connection on smartphones and edge devices with very low memory. That is, now AI features that previously ran on powerful cloud infrastructure can be run directly on phones and low-power devices.

Gemma 3n's special technology is MatFormer.

The heart of Gemma 3n is its new architecture MatFormer, full name Matryoshka Transformer. It works like Russian nesting dolls, with smaller fully-functional sub-models inside a larger model. The advantage of this is that developers can scale the model according to the capacity of their device. Gemma 3n has been introduced in two variants. One is E2B which requires only 2GB of RAM and the other is E4B which requires about 3GB of RAM.

Amazing performance even in small RAM
Gemma 3n has 5 to 8 billion raw parameters, but its design is so efficient that it uses resources like smaller models. Its secret is Per-Layer Embeddings (PLE) technology, which removes work from the phone's graphics processor (GPU) and transfers it to the CPU. This saves a lot of memory. Due to the KV Cache Sharing feature, the speed of processing long audio and video inputs increases up to 2 times.

Audio and Voice Features
It has a built-in audio encoder taken from Google's Universal Speech Model. It can do speech-to-text and language translation on the phone itself. It gives excellent results, especially in translation from English to European languages ​​​​like Spanish, French, Italian, and Portuguese. The vision side is powered by Google's new MobileNet-V5 lightweight vision encoder.

It can process video streams at up to 60 FPS, making real-time video analysis extremely smooth on devices like Google Pixel. It is both faster and more accurate than previous vision models. Most importantly, Gemma 3n can work completely offline, meaning it does not require the internet. This is extremely beneficial for places where there is no internet or there is a greater need for privacy.

Disclaimer: This content has been sourced and edited from Amar Ujala. While we have made modifications for clarity and presentation, the original content belongs to its respective authors and website. We do not claim ownership of the content.

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