Predictive APIs and Machine Learning Integration
Introducing Gemma 3 270M: The compact model for hyper-efficient AI- Google Developers Blog

Introducing Gemma 3 270M: The compact model for hyper-efficient AI- Google Developers Blog

8/14/2025 · Olivier Lacombe, Kathleen Kenealy, Kat Black, Ravin Kumar, Francesco Visin, Jiageng Zhang

What this post added

Introduced Gemma 3 270M, a compact 270-million parameter model designed for task-specific fine-tuning. It features a large vocabulary (256k tokens) for handling specific tokens, extreme energy efficiency (0.75% battery usage on Pixel 9 Pro SoC for 25 conversations with INT4 quantization), strong instruction-following capabilities out-of-the-box, and production-ready Quantization-Aware Trained (QAT) checkpoints for INT4 precision deployment on resource-constrained devices. The model is positioned as the 'right tool for the job' for high-volume, well-defined tasks, cost-sensitive applications, rapid iteration, user privacy on-device, and building fleets of specialized models.

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