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.

Qwen2-VL-72B-Instruct
Alibaba
Qwen2-VL-72B-Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 75.8% across 15 benchmarks. It excels particularly in DocVQAtest (96.5%), VCR_en_easy (91.9%), ChartQA (88.3%). The model shows particular specialization in general tasks with an average performance of 82.2%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Qwen2-VL-72B-Instruct
Alibaba
2024-08-29

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

Gemini 2.5 Pro

Qwen2-VL-72B-Instruct
Performance comparison across key benchmark categories

Gemini 2.5 Pro

Qwen2-VL-72B-Instruct
Qwen2-VL-72B-Instruct
2023-06-30
Gemini 2.5 Pro
2025-01-31
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.5 Pro

Qwen2-VL-72B-Instruct

Gemini 2.5 Pro

Qwen2-VL-72B-Instruct