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 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.

Google

Gemma 2 27B

Google

2024-06-27

Google

Gemini 2.0 Flash Thinking

Google

2025-01-21

6 months newer

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash Thinking

general
+3.8%
73.8%
Google

Gemma 2 27B

general
70.0%
Knowledge Cutoff
Training data recency comparison

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 2 27B

0 providers
Google

Gemini 2.0 Flash Thinking

Avg Score:0.0%
Providers:0
Google

Gemma 2 27B

Avg Score:0.0%
Providers:0