Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 3.4% higher average benchmark score. 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 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.
2 months newer
Gemma 3 4B
2025-03-12
Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20
Context window and performance specifications
Average performance across 44 common benchmarks
Gemma 3 4B
Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Gemma 3 4B
2024-08-01
Available providers and their performance metrics
Gemma 3 4B
DeepInfra
Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3 4B
Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3 4B
Gemma 3n E2B Instructed LiteRT (Preview)