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-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

DeepSeek VL2
DeepSeek
2024-12-13
3 months newer
Performance Metrics
Context window and performance specifications

DeepSeek VL2

Qwen2-VL-72B-Instruct
Average performance across 4 common benchmarks

DeepSeek VL2

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

DeepSeek VL2

Qwen2-VL-72B-Instruct
Qwen2-VL-72B-Instruct
2023-06-30
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek VL2
Replicate

Qwen2-VL-72B-Instruct

DeepSeek VL2

Qwen2-VL-72B-Instruct