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-Omni-7B

Alibaba

Qwen2.5-Omni-7B is a multimodal language model developed by Alibaba. The model shows competitive results across 45 benchmarks. It excels particularly in DocVQA (95.2%), VocalSound (93.9%), GSM8k (88.7%). The model shows particular specialization in code tasks with an average performance of 76.0%. 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.

Alibaba

Qwen2.5-Omni-7B

Alibaba

2025-03-27

Google

Gemma 3n E4B

Google

2025-06-26

3 months newer

Performance comparison across key benchmark categories

Google

Gemma 3n E4B

general
+1.0%
59.6%
Alibaba

Qwen2.5-Omni-7B

general
58.7%
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-Omni-7B

0 providers
Google

Gemma 3n E4B

Avg Score:0.0%
Providers:0
Alibaba

Qwen2.5-Omni-7B

Avg Score:0.0%
Providers:0