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

DeepSeek VL2
DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). The model shows particular specialization in vision tasks with an average performance of 76.7%. It supports a 259K token context window for handling large documents. 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 DeepSeek'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.

DeepSeek VL2
DeepSeek
2024-12-13

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

DeepSeek VL2

Gemini 2.5 Pro
Performance Metrics
Context window and performance specifications

DeepSeek VL2

Gemini 2.5 Pro
Average performance across 1 common benchmarks

DeepSeek VL2

Gemini 2.5 Pro
Performance comparison across key benchmark categories

DeepSeek VL2

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

DeepSeek VL2
Replicate

Gemini 2.5 Pro

DeepSeek VL2

Gemini 2.5 Pro