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.
Jamba 1.5 Large
AI21 Labs
Jamba 1.5 Large is a language model developed by AI21 Labs. It achieves strong performance with an average score of 65.5% across 8 benchmarks. It excels particularly in ARC-C (93.0%), GSM8k (87.0%), MMLU (81.2%). It supports a 512K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents AI21 Labs's latest advancement in AI technology.
Jamba 1.5 Large
AI21 Labs
2024-08-22

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

Gemma 3n E2B Instructed LiteRT (Preview)
Jamba 1.5 Large
Average performance across 4 common benchmarks

Gemma 3n E2B Instructed LiteRT (Preview)
Jamba 1.5 Large
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed LiteRT (Preview)
Jamba 1.5 Large
Jamba 1.5 Large
2024-03-05
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B Instructed LiteRT (Preview)
Jamba 1.5 Large
Bedrock

Gemma 3n E2B Instructed LiteRT (Preview)
Jamba 1.5 Large