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

Gemma 3n E4B
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.

Qwen2.5 VL 32B Instruct
Alibaba
Qwen2.5 VL 32B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 63.6% across 28 benchmarks. It excels particularly in DocVQA (94.8%), Android Control Low_EM (93.3%), HumanEval (91.5%). The model shows particular specialization in code tasks with an average performance of 87.8%. 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 2025, it represents Alibaba's latest advancement in AI technology.

Qwen2.5 VL 32B Instruct
Alibaba
2025-02-28

Gemma 3n E4B
2025-06-26
3 months newer
Performance comparison across key benchmark categories

Gemma 3n E4B

Qwen2.5 VL 32B Instruct
Gemma 3n E4B
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E4B

Qwen2.5 VL 32B Instruct

Gemma 3n E4B

Qwen2.5 VL 32B Instruct