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.

GPT-5 nano
OpenAI
GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.

DeepSeek VL2
DeepSeek
2024-12-13

GPT-5 nano
OpenAI
2025-08-07
7 months newer
Pricing Comparison
Cost per million tokens (USD)

DeepSeek VL2

GPT-5 nano
Performance Metrics
Context window and performance specifications

DeepSeek VL2

GPT-5 nano
Performance comparison across key benchmark categories

DeepSeek VL2

GPT-5 nano
GPT-5 nano
2024-05-30
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek VL2
Replicate

GPT-5 nano
ZeroEval
OpenAI

DeepSeek VL2

GPT-5 nano