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DeepSeek-VL2

DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

View on GitHub Official site
Vision Multimodal MIT Hard setup 5,316 stars

Overview

Description

DeepSeek-VL2 lets your applications see and reason about images, documents, tables, and charts through natural conversation. It handles visual question answering, OCR, and document analysis with advanced accuracy while using fewer compute resources than comparable models. The bottom line: add multimodal understanding to your product efficiently.

Technical scorecard

License

MIT

Commercial use

Yes

OpenAI-compatible API

No

REST API

No

Fine-tuning support

No

Quantization support

No

Docker available

No

GUI / no-code available

Yes

Telemetry

Unknown

Offline after setup

Yes

Data & Privacy

Does it send data online?

After setup, this listing is marked as usable offline. Confirm network behavior against the upstream project before regulated deployment.

Does it store history?

Not verified in this directory yet. Review the upstream docs for persistence, logs, and workspace storage.

License checks?

Commercial use is marked as allowed or likely allowed by the listed license.

Telemetry?

Unknown

Last verified: Jul 22, 2026. Maintainer verification should be treated as directory guidance, not legal advice.

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Setup & Installation

Hard

A developer can usually get this running with standard docs.

# Start with the official project repository
# https://github.com/deepseek-ai/DeepSeek-VL2

Hardware Requirements

Hardware tagsGPU (NVIDIA)
LanguagesPython

Works Well With