DeepSeek-VL-1.3|7B
FreeOpen-source vision-language model series for real-world understanding
FreeFree tier
Inputs: image, textOutputs: text
About DeepSeek-VL-1.3|7B
DeepSeek-VL is an open-source series of vision-language models developed by DeepSeek AI, designed for real-world image-text-to-text understanding tasks. Available in 2B and 7B parameter sizes, these models excel at processing both images and text to generate accurate textual outputs. Built on the DeepSeek architecture, the series targets practical applications such as visual question answering, image captioning, and document understanding. The models are hosted on Hugging Face as a collection, with a corresponding research paper (arXiv 2403.05525) published in March 2024.
Key Features
Image-text-to-text generation
Model sizes: 2B and 7B parameters
Open-source and freely available on Hugging Face
Based on DeepSeek architecture
Supported by research paper (arXiv 2403.05525)
Pros & Cons
Pros
- Open-source with permissive licensing
- Multiple model sizes for different compute budgets
- Strong performance on real-world vision-language benchmarks
- Backed by a dedicated research team (DeepSeek AI)
Cons
- Limited documentation compared to larger multimodal models
- 7B model requires significant GPU memory for inference
- May inherit biases from training data
Best For
Visual question answeringImage captioningDocument understanding and OCRMultimodal reasoning tasksReal-world vision-language applications
FAQ
What is DeepSeek-VL?
DeepSeek-VL is a series of open-source vision-language models developed by DeepSeek AI, designed for image-text-to-text tasks such as visual question answering and image captioning.
What model sizes are available?
The collection includes 2B and 7B parameter versions, as seen on the Hugging Face page.
Is DeepSeek-VL free to use?
Yes, the models are open-source and freely available on Hugging Face, with no pricing listed.
How can I access or use these models?
The models are hosted on Hugging Face in the deepseek-ai collection. Users can download them directly or integrate via Hugging Face libraries.
What type of input does the model accept?
It accepts image and text input, as indicated by the 'Image-Text-to-Text' classification.