I am currently using the Q4_K_M quantized version of gemma-3-27b-it locally. I previously assumed that a 27B model with image input support wouldn't be very high quality, but after actually using it, the generated responses feel better than those from my previously used DeepSeek-R1-Distill-Qwen-32B (Q4_K_M), and its recognition of images is also stronger than I expected. (I thought the model could only roughly understand the concepts in the image, but I didn't expect it to be able to recognize text within the image.)
Since this article publishes the optimized Q4 quantized version, it would be great if it included more comparisons between the new version and my currently used unoptimized Q4 version (such as benchmark scores).
(I deliberately wrote this reply in Chinese and had gemma-3-27b-it Q4_K_M translate it into English.)
Since this article publishes the optimized Q4 quantized version, it would be great if it included more comparisons between the new version and my currently used unoptimized Q4 version (such as benchmark scores).
(I deliberately wrote this reply in Chinese and had gemma-3-27b-it Q4_K_M translate it into English.)