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

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.

QvQ-72B-Preview
Alibaba
QvQ-72B-Preview is a multimodal language model developed by Alibaba. The model shows competitive results across 4 benchmarks. Notable strengths include MathVista (71.4%), MMMU (70.3%), MathVision (35.9%). 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 2024, it represents Alibaba's latest advancement in AI technology.

QvQ-72B-Preview
Alibaba
2024-12-25

Gemini 2.5 Pro
2025-05-20
4 months newer
Performance Metrics
Context window and performance specifications

Gemini 2.5 Pro

QvQ-72B-Preview
Average performance across 1 common benchmarks

Gemini 2.5 Pro

QvQ-72B-Preview
Performance comparison across key benchmark categories

Gemini 2.5 Pro

QvQ-72B-Preview
Gemini 2.5 Pro
2025-01-31
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.5 Pro

QvQ-72B-Preview

Gemini 2.5 Pro

QvQ-72B-Preview