Comprehensive side-by-side LLM comparison
Gemma 3n E2B Instructed LiteRT (Preview) leads with 2.9% higher average benchmark score. Gemini 2.5 Pro is available on 2 providers. Both models have their strengths depending on your specific coding needs.
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. 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.
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.
Launched on the same date
Gemini 2.5 Pro
2025-05-20
Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20
Context window and performance specifications
Average performance across 40 common benchmarks
Gemini 2.5 Pro
Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Pro
ZeroEval
Gemini 2.5 Pro
Gemma 3n E2B Instructed LiteRT (Preview)
Gemini 2.5 Pro
Gemma 3n E2B Instructed LiteRT (Preview)
Gemma 3n E2B Instructed LiteRT (Preview)