Google launches its latest open AI models

Google has launched Gemma 3, the latest version of its family of open AI models that aim to set a new benchmark for AI accessibility.…

Google has launched Gemma 3, the latest version of its family of open AI models that aim to set a new benchmark for AI accessibility.

Built upon the foundations of the company’s Gemini 2.0 models, Gemma 3 is engineered to be lightweight, portable, and adaptable—enabling developers to create AI applications across a wide range of devices.  

This release comes hot on the heels of Gemma’s first birthday, an anniversary underscored by impressive adoption metrics. Gemma models have achieved more than 100 million downloads and spawned the creation of over 60,000 community-built variants. Dubbed the “Gemmaverse,” this ecosystem signals a thriving community aiming to democratise AI.  

“The Gemma family of open models is foundational to our commitment to making useful AI technology accessible,” explained Google.

Gemma 3 models are available in various sizes – 1B, 4B, 12B, and 27B parameters – allowing developers to select a model tailored to their specific hardware and performance requirements. These models promise faster execution, even on modest computational setups, without compromising functionality or accuracy.

The model’s performance advantages are clearly illustrated in the Chatbot Arena Elo Score leaderboard. Despite requiring just a single NVIDIA H100 GPU, the flagship 27B version of Gemma 3 ranks among the top chatbots, achieving an Elo score of 1338. Many competitors demand up to 32 GPUs to deliver comparable performance.

One of Gemma 3’s strengths lies in its adaptability within developers’ existing workflows.  

For immediate experiments, users can access Gemma 3 models via platforms such as Hugging Face and Kaggle, or take advantage of the Google AI Studio for in-browser deployment.

“We believe open models require careful risk assessment, and our approach balances innovation with safety,” explains Google.  

Gemma 3’s team adopted stringent governance policies, applying fine-tuning and robust benchmarking to align the model with ethical guidelines. Given the models enhanced capabilities in STEM fields, it underwent specific evaluations to mitigate risks of misuse, such as generating harmful substances.

Google is pushing for collective efforts within the industry to create proportionate safety frameworks for increasingly powerful models.