Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance

Gemma 2 27B
Gemma 2 27B is a language model developed by Google. It achieves strong performance with an average score of 69.1% across 16 benchmarks. It excels particularly in ARC-E (88.6%), HellaSwag (86.4%), BoolQ (84.8%). The model shows particular specialization in reasoning tasks with an average performance of 82.5%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Google's latest advancement in AI technology.

QvQ-72B-Preview
Alibaba
QvQ-72B-Preview is a multimodal language model developed by Alibaba. The model shows competitive results across 4 benchmarks. Notable strengths include MathVista (71.4%), MMMU (70.3%), MathVision (35.9%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Gemma 2 27B
2024-06-27

QvQ-72B-Preview
Alibaba
2024-12-25
6 months newer
Performance comparison across key benchmark categories

Gemma 2 27B

QvQ-72B-Preview
Provider Availability & Performance
Available providers and their performance metrics

Gemma 2 27B

QvQ-72B-Preview

Gemma 2 27B

QvQ-72B-Preview