Google has introduced Gemma 2, the latest addition to its lineup of open Large Language Models (LLMs). Available in two sizes—9 billion (9B) and 27 billion (27B) parameters—Gemma 2 models come in both base and instruction-tuned versions. Trained on a significantly larger dataset compared to their predecessors, these models boast several cutting-edge advancements such as sliding window attention, logit soft-capping, knowledge distillation, and model merging techniques.
Integrated with Hugging Face Transformers and accessible via Google Cloud and Vertex AI, Gemma 2 is particularly optimized for dialogue applications. The models support various fine-tuning and deployment options, offering substantial flexibility for developers.
The 9B model outperforms Llama-3’s 8B model in numerous benchmarks, while the 27B model holds its own against larger models, even those with 70 billion parameters. Both models are engineered to run on specific hardware, including Nvidia H100, A100 with 80GB VRAM, or TPUs, and excel in chain-of-thought reasoning and step-by-step explanations.
These models are designed not only for efficiency and speed but also for versatility across a wide array of applications—from customer service automation to content creation and language translation. Furthermore, Google plans to make these models more accessible through Google Cloud and Vertex AI, and has hinted at potentially open-sourcing text watermarking technology in the future.
Whether you’re a developer looking to integrate advanced LLM capabilities into your applications or an organization aiming to leverage the power of AI, the Gemma 2 series offers robust, scalable solutions.

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Google has introduced Gemma 2, advanced Large Language Models available in 9 billion (9B) and 27 billion (27B) parameters. These models include state-of-the-art techniques like sliding window attention and knowledge distillation, and are optimized for various applications such as dialogue systems and content creation. Gemma 2 integrates with Hugging Face Transformers and is accessible via Google Cloud and Vertex AI. Notably, the 9B model outperforms Llama-3's 8B model in benchmarks, and the 27B model competes with models up to 70 billion parameters.

Introducing Google's Gemma 2: Advanced Open LLM Models in 9B and 27B Sizes