Microsoft’s loralib implements low rank adaptation for large language models.
Open source
24 alternativesDeepSeek-VL2
DeepSeek-VL2 supports multimodal understanding through a mixture-of-experts vision-language model.
About DeepSeek-VL2
DeepSeek-VL2 is an open-source series of vision-language models that use a mixture-of-experts architecture to process images together with text. The repository describes the models as improving on the predecessor DeepSeek-VL. The stated tasks include visual question answering, optical character recognition, document, table and chart understanding, and visual grounding.
The series has three variants, DeepSeek-VL2-Tiny, DeepSeek-VL2-Small and DeepSeek-VL2, with 1.0B, 2.8B and 4.5B activated parameters. The repository includes a Python inference example for single-image conversations and says the model should run with the required dependencies installed. The source notes that running the Small variant may need 80GB of GPU memory, and more for the full model. Use of the models is subject to the license terms in the repository.
Key features
- Visual question answering, optical character recognition, and document, table and chart understanding
- Visual grounding with object localization using reference tokens in prompts
- Grounded captioning that combines object localization with reasoning, enabled by a special prompt token
- Three model variants with 1.0B, 2.8B and 4.5B activated parameters
- Incremental prefilling support
- Python inference example for single-image conversations
Best for: Researchers and developers who want an open-source vision-language model for document, chart and image understanding tasks and have access to GPU hardware.
Good for
- Open-source code and model release, with the model series available for download on Hugging Face
- The source reports competitive or state-of-the-art performance with similar or fewer activated parameters than some comparable open-source models
Watch out for
- The source notes that running the Small model may need 80GB of GPU memory, with more needed for the full model
- Use of the model is subject to the terms in the license section of the repository
- The listed sequence length is 4096 for all three variants
DeepSeek-VL2 at a glance
- Category
- AI & Machine Learning › Models & ML Research
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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DeepSeek-VL2 FAQ
What Python version is required?
The installation instructions state that the setup is based on a Python 3.8 or later environment.
How is the repository installed?
The quick start section installs the dependencies by running pip install -e . in the repository.
How much GPU memory is needed?
The source notes that running the Small model may need 80GB of GPU memory, and that the full DeepSeek-VL2 model needs even more.
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