Google’s new offline AI model breaking records

Google has just unveiled new AI model which is breaking expectations about what small models can do.

The tech giant company, Google just shocked the AI world with its newly launched tiny Artificial Intelligence (AI) model named “Embedding Gemma” an offline-AI application.

Embedding Gemma has only 308 million parameters but it delivering results and beating models twice its size on the toughest benchmarks.

It has grabbed everyone’s attention with its size and the fastest speed it offers. With smart training the Embedding Gemma runs fully offline on devices with 200 MB RAM, as small as phones, or as simple as laptops and still manages a sub-15 millisecond response time on specialized hardware.

Moreover, on top of that, with multi-lingual embedding training the new AI-offline model understands more than 100 languages and tops up the benchmark chart with 500 billion parameters.

The embedding Gemma 3 is considered to be Google’s most practical AI tool release yet.

Furthermore, it scales down vectors without loosing power, making it perfect for private search, RAG pipelines and fine-tuning on everyday GPUs with the help of Matryoshka Learning models.

Offline-AI:

Offline AI refers to the machine-learning models that run directly on a user’s device rather than on remote cloud servers. Google explains on-device AI as enabling features like summaries, translations, image understanding and voice processing without needing continuous internet access.

It majorly relies on two technical aspects such as smaller, optimized model architectures designed for constrained hardware and mobile SoCs (system on chip) with dedicated NPU and ML accelerators that can execute those models efficiently.

Why it matters?

IN 2025, Google expanded its on device offline AI offering models so that smart phones and other devices can run generative and multimodal models locally.

The goal was to introduce lower latency, improved privacy and continued functionality with a network connection.

Google new Embedding Gemma model holds a significant importance, its not only about its size but also about making AI private, efficient and usable on other devices. Google aims to hold the future of AI not only in Cloud but also accessible for everyone.