Feed: Slashdot
Feed Link: https://slashdot.org/
---

Title: Google Releases Pint-Size Gemma Open AI Model

Link: https://tech.slashdot.org/story/25/08/14/2150...

An anonymous reader quotes a report from Ars Technica: Google has announced a
tiny version of its Gemma open model designed to run on local devices. Google
says the new Gemma 3 270M can be tuned in a snap and maintains robust
performance despite its small footprint. [...] Running an AI model locally
has numerous benefits, including enhanced privacy and lower latency. Gemma 3
270M was designed with these kinds of use cases in mind. In testing with a
Pixel 9 Pro, the new Gemma was able to run 25 conversations on the Tensor G4
chip and use just 0.75 percent of the device's battery. That makes it by far
the most efficient Gemma model. Developers shouldn't expect the same
performance level of a multi-billion-parameter model, but Gemma 3 270M has
its uses. Google used the IFEval benchmark, which tests a model's ability to
follow instructions, to show that its new model punches above its weight.
Gemma 3 270M hits a score of 51.2 percent in this test, which is higher than
other lightweight models that have more parameters. The new Gemma falls
predictably short of 1 billion-plus models like Llama 3.2, but it gets closer
than you might think for having just a fraction of the parameters. Google
claims Gemma 3 270M is good at following instructions out of the box, but it
expects developers to fine-tune the model for their specific use cases. Due
to the small parameter count, that process is fast and low-cost, too. Google
sees the new Gemma being used for tasks like text classification and data
analysis, which it can accomplish quickly and without heavy computing
requirements. You can download the new Gemma for free, and the model weights
are available. There's no separate commercial licensing agreement, so
developers can modify, publish, and deploy Gemma 3 270M derivatives in their
tools. You can download Gemma 3 270M from Hugging Face and Kaggle in both pre-
trained and instruction-tuned versions.

Read more of this story at Slashdot.

---
VRSS v2.1.180528