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.
Jamba 1.5 Mini
AI21 Labs
Jamba 1.5 Mini is a language model developed by AI21 Labs. The model shows competitive results across 8 benchmarks. It excels particularly in ARC-C (85.7%), GSM8k (75.8%), MMLU (69.7%). 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 Mini
AI21 Labs
2024-08-22

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

Gemma 3n E4B
Jamba 1.5 Mini
Average performance across 1 common benchmarks

Gemma 3n E4B
Jamba 1.5 Mini
Performance comparison across key benchmark categories

Gemma 3n E4B
Jamba 1.5 Mini
Jamba 1.5 Mini
2024-03-05
Gemma 3n E4B
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E4B
Jamba 1.5 Mini
Bedrock

Gemma 3n E4B
Jamba 1.5 Mini