Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. 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.
Gemma 3n E4B Instructed LiteRT Preview is a multimodal language model developed by Google. The model shows competitive results across 28 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.
2 months newer
Gemma 3 4B
2025-03-12
Gemma 3n E4B Instructed LiteRT Preview
2025-05-20
Context window and performance specifications
Average performance across 44 common benchmarks
Gemma 3 4B
Gemma 3n E4B Instructed LiteRT Preview
Gemma 3n E4B Instructed LiteRT Preview
2024-06-01
Gemma 3 4B
2024-08-01
Available providers and their performance metrics
Gemma 3 4B
DeepInfra
Gemma 3n E4B Instructed LiteRT Preview
Gemma 3 4B
Gemma 3n E4B Instructed LiteRT Preview
Gemma 3 4B
Gemma 3n E4B Instructed LiteRT Preview