Model Comparison

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

Google

Gemini 2.0 Flash Thinking

Google

Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). 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.

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.

Google

Gemini 2.0 Flash Thinking

Google

2025-01-21

Google

Gemma 3n E4B

Google

2025-06-26

5 months newer

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash Thinking

general
+14.1%
73.8%
Google

Gemma 3n E4B

general
59.6%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B

2024-06-01

Gemini 2.0 Flash Thinking

2024-08-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.0 Flash Thinking

0 providers
Google

Gemma 3n E4B

0 providers
Google

Gemini 2.0 Flash Thinking

Avg Score:0.0%
Providers:0
Google

Gemma 3n E4B

Avg Score:0.0%
Providers:0