Model Comparison

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

Google

Gemma 3n E4B

Google

Gemma 3n E4B is a multimodal language model developed by Google. It achieves strong performance with an average score of 64.6% across 11 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

Alibaba

Qwen2.5 VL 72B Instruct

Alibaba

Qwen2.5 VL 72B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 66.9% across 30 benchmarks. It excels particularly in DocVQA (96.4%), Android Control Low_EM (93.7%), ChartQA (89.5%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5 VL 72B Instruct

Alibaba

2025-01-26

Google

Gemma 3n E4B

Google

2025-06-26

5 months newer

Performance comparison across key benchmark categories

Google

Gemma 3n E4B

general
59.6%
Alibaba

Qwen2.5 VL 72B Instruct

general
+10.0%
69.6%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 3n E4B

0 providers
Alibaba

Qwen2.5 VL 72B Instruct

0 providers
Google

Gemma 3n E4B

Avg Score:0.0%
Providers:0
Alibaba

Qwen2.5 VL 72B Instruct

Avg Score:0.0%
Providers:0