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.

Qwen2.5-Omni-7B
Alibaba
Qwen2.5-Omni-7B is a multimodal language model developed by Alibaba. The model shows competitive results across 45 benchmarks. It excels particularly in DocVQA (95.2%), VocalSound (93.9%), GSM8k (88.7%). The model shows particular specialization in code tasks with an average performance of 76.0%. 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 Alibaba's latest advancement in AI technology.

DeepSeek VL2
DeepSeek
2024-12-13

Qwen2.5-Omni-7B
Alibaba
2025-03-27
3 months newer
Performance Metrics
Context window and performance specifications

DeepSeek VL2

Qwen2.5-Omni-7B
Average performance across 9 common benchmarks

DeepSeek VL2

Qwen2.5-Omni-7B
Performance comparison across key benchmark categories

DeepSeek VL2

Qwen2.5-Omni-7B
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek VL2
Replicate

Qwen2.5-Omni-7B

DeepSeek VL2

Qwen2.5-Omni-7B