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

Gemma 3n E4B
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.

Llama 3.2 90B Instruct
Meta
Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. 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 2024, it represents Meta's latest advancement in AI technology.

Llama 3.2 90B Instruct
Meta
2024-09-25

Gemma 3n E4B
2025-06-26
9 months newer
Performance Metrics
Context window and performance specifications

Gemma 3n E4B

Llama 3.2 90B Instruct
Performance comparison across key benchmark categories

Gemma 3n E4B

Llama 3.2 90B Instruct
Gemma 3n E4B
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E4B

Llama 3.2 90B Instruct
Together
Hyperbolic
DeepInfra
Fireworks
Bedrock

Gemma 3n E4B

Llama 3.2 90B Instruct