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-mini-instruct
Microsoft
Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. 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-mini-instruct
Microsoft
2024-08-23

DeepSeek VL2
DeepSeek
2024-12-13
3 months newer
Pricing Comparison
Cost per million tokens (USD)

DeepSeek VL2

Phi-3.5-mini-instruct
Performance Metrics
Context window and performance specifications

DeepSeek VL2

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

DeepSeek VL2

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

DeepSeek VL2
Replicate

Phi-3.5-mini-instruct
Azure

DeepSeek VL2

Phi-3.5-mini-instruct