Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance

Gemini 2.5 Flash
Gemini 2.5 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 14 benchmarks. It excels particularly in Global-MMLU-Lite (88.4%), AIME 2024 (88.0%), FACTS Grounding (85.3%). 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 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.

Gemini 2.5 Flash
2025-05-20

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

Gemini 2.5 Flash

Gemma 3n E4B
Performance comparison across key benchmark categories

Gemini 2.5 Flash

Gemma 3n E4B
Gemma 3n E4B
2024-06-01
Gemini 2.5 Flash
2025-01-31
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.5 Flash
ZeroEval

Gemma 3n E4B

Gemini 2.5 Flash

Gemma 3n E4B