Model Comparison

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

Google

Gemma 2 27B

Google

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.

Alibaba

Qwen2-VL-72B-Instruct

Alibaba

Qwen2-VL-72B-Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 75.8% across 15 benchmarks. It excels particularly in DocVQAtest (96.5%), VCR_en_easy (91.9%), ChartQA (88.3%). The model shows particular specialization in general tasks with an average performance of 82.2%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Google

Gemma 2 27B

Google

2024-06-27

Alibaba

Qwen2-VL-72B-Instruct

Alibaba

2024-08-29

2 months newer

Performance comparison across key benchmark categories

Google

Gemma 2 27B

general
70.0%
math
58.1%
Alibaba

Qwen2-VL-72B-Instruct

general
+12.2%
82.2%
math
+12.4%
70.5%
Knowledge Cutoff
Training data recency comparison

Qwen2-VL-72B-Instruct

2023-06-30

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 2 27B

0 providers
Alibaba

Qwen2-VL-72B-Instruct

0 providers
Google

Gemma 2 27B

Avg Score:0.0%
Providers:0
Alibaba

Qwen2-VL-72B-Instruct

Avg Score:0.0%
Providers:0