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

Gemini 2.0 Flash
Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Google's latest advancement in AI technology.

Gemini 2.5 Pro
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 67.1% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). The model shows particular specialization in vision tasks with an average performance of 82.2%. With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. 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 2.0 Flash
2024-12-01

Gemini 2.5 Pro
2025-05-20
5 months newer
Pricing Comparison
Cost per million tokens (USD)

Gemini 2.0 Flash

Gemini 2.5 Pro
Performance Metrics
Context window and performance specifications

Gemini 2.0 Flash

Gemini 2.5 Pro
Average performance across 4 common benchmarks

Gemini 2.0 Flash

Gemini 2.5 Pro
Performance comparison across key benchmark categories

Gemini 2.0 Flash

Gemini 2.5 Pro
Gemini 2.0 Flash
2024-08-01
Gemini 2.5 Pro
2025-01-31
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.0 Flash

Gemini 2.5 Pro

Gemini 2.0 Flash

Gemini 2.5 Pro