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.

Granite 3.3 8B Base
IBM
Granite 3.3 8B Base is a multimodal language model developed by IBM. It achieves strong performance with an average score of 64.3% across 20 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). 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 IBM's latest advancement in AI technology.

Granite 3.3 8B Base
IBM
2025-04-16

Gemini 2.5 Pro
2025-05-20
1 month newer
Performance Metrics
Context window and performance specifications

Gemini 2.5 Pro

Granite 3.3 8B Base
Average performance across 1 common benchmarks

Gemini 2.5 Pro

Granite 3.3 8B Base
Performance comparison across key benchmark categories

Gemini 2.5 Pro

Granite 3.3 8B Base
Granite 3.3 8B Base
2024-04-01
Gemini 2.5 Pro
2025-01-31
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.5 Pro

Granite 3.3 8B Base

Gemini 2.5 Pro

Granite 3.3 8B Base