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.

IBM

Granite 3.3 8B Base

IBM

Granite 3.3 8B Base is a multimodal language model developed by IBM. It achieves strong performance with an average score of 64.3% across 20 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). 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 IBM's latest advancement in AI technology.

IBM

Granite 3.3 8B Base

IBM

2025-04-16

Google

Gemma 3n E4B

Google

2025-06-26

2 months newer

Average performance across 6 common benchmarks

Google

Gemma 3n E4B

+1.2%
Average Score:66.0%
IBM

Granite 3.3 8B Base

Average Score:64.8%

Performance comparison across key benchmark categories

Google

Gemma 3n E4B

reasoning
+4.9%
73.4%
general
59.6%
IBM

Granite 3.3 8B Base

reasoning
68.4%
general
+0.1%
59.7%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Granite 3.3 8B Base

2024-04-01

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
IBM

Granite 3.3 8B Base

0 providers
Google

Gemma 3n E4B

+1.2%
Avg Score:66.0%
Providers:0
IBM

Granite 3.3 8B Base

Avg Score:64.8%
Providers:0