Google S Lightweight Gemma 3 Open Model Nearly Matches Deepseek R1

Except for the smallest Gemma 3 1B model, all models are inherently multimodal meaning they can process images and videos as well. Not only that, Gemma 3 models are multilingual and support over 140 languages. Despite the small size, Google has done a commendable job packing so much knowledge into a small footprint.
As for performance, the largest 27B model outperforms significantly larger models such as DeepSeek V3 671B, Llama 3.1 405B, Mistral Large, and o3-mini in the LMSYS Chatbot Arena. Gemma 3 27B achieved an Elo score of 1,338 on the Chatbot Arena and ranks just below the DeepSeek R1 reasoning model which scored 1,363.
It’s quite astonishing to see that such a small model is performing along the lines of frontier models. Google says it has used “a novel post-training approach that brings gains across all capabilities, including math, coding, chat, instruction following, and multilingual.“
On top of that, Gemma 3 models are trained on an improved version of knowledge distillation. As a result, the 27B model almost matches Gemini 1.5 Flash performance. Finally, Gemma 3 models have a context window of 128K, and bring support for function calling, and structured output. It looks like Google has delivered a very competitive open model in a small size to take on DeepSeek R1 and Llama 3 405B models. Developers would be quite happy to use Gemma 3 which is multimodal and multilingual with the ability to host open weights.