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.

Gemma 3n E4B
Gemma 3n E4B is a multimodal language model developed by Google. It achieves strong performance with an average score of 64.6% across 11 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). 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

Gemma 3n E4B
2025-06-26
6 months newer
Performance Metrics
Context window and performance specifications

DeepSeek VL2

Gemma 3n E4B
Performance comparison across key benchmark categories

DeepSeek VL2

Gemma 3n E4B
Gemma 3n E4B
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek VL2
Replicate

Gemma 3n E4B

DeepSeek VL2

Gemma 3n E4B