Model Comparison

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

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.

Gemma 3n E2B Instructed

Google

Gemma 3n E2B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (66.5%), MMLU (60.1%), Global-MMLU-Lite (59.0%). 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.

Gemma 2 27B

Google

2024-06-27

Gemma 3n E2B Instructed

Google

2025-06-26

12 months newer

Average performance across 3 common benchmarks

Gemma 2 27B

+2.1%

Average Score:63.2%

Gemma 3n E2B Instructed

Average Score:61.1%

Performance comparison across key benchmark categories

Gemma 2 27B

general

+37.2%

70.0%

math

+17.7%

58.1%

code

+23.3%

56.5%

Gemma 3n E2B Instructed

general

32.8%

math

40.4%

code

33.2%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Knowledge Cutoff

Training data recency comparison

Gemma 3n E2B Instructed

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Gemma 2 27B

0 providers

Gemma 3n E2B Instructed

0 providers

Gemma 2 27B

+2.1%

Avg Score:63.2%

Providers:0

Gemma 3n E2B Instructed

Avg Score:61.1%

Providers:0