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

Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3n E2B Instructed LiteRT (Preview) is a multimodal language model developed by Google. The model shows competitive results across 28 benchmarks. Notable strengths include PIQA (78.9%), BoolQ (76.4%), ARC-E (75.8%). 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 Google's latest advancement in AI technology.

Llama 3.2 3B Instruct
Meta
Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta's latest advancement in AI technology.

Llama 3.2 3B Instruct
Meta
2024-09-25

Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20
7 months newer
Performance Metrics
Context window and performance specifications

Gemma 3n E2B Instructed LiteRT (Preview)

Llama 3.2 3B Instruct
Average performance across 5 common benchmarks

Gemma 3n E2B Instructed LiteRT (Preview)

Llama 3.2 3B Instruct
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed LiteRT (Preview)

Llama 3.2 3B Instruct
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B Instructed LiteRT (Preview)

Llama 3.2 3B Instruct
DeepInfra

Gemma 3n E2B Instructed LiteRT (Preview)

Llama 3.2 3B Instruct