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.

Phi-3.5-MoE-instruct
Microsoft
Phi-3.5-MoE-instruct is a language model developed by Microsoft. It achieves strong performance with an average score of 65.6% across 31 benchmarks. It excels particularly in ARC-C (91.0%), OpenBookQA (89.6%), GSM8k (88.7%). The model shows particular specialization in reasoning tasks with an average performance of 85.4%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Phi-3.5-MoE-instruct
Microsoft
2024-08-23

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

DeepSeek VL2

Phi-3.5-MoE-instruct
Performance comparison across key benchmark categories

DeepSeek VL2

Phi-3.5-MoE-instruct
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek VL2
Replicate

Phi-3.5-MoE-instruct

DeepSeek VL2

Phi-3.5-MoE-instruct