What are the hardware requirements for Deepseek Vl2 Tiny 6bit?

Deepseek Vl2 Tiny 6bit requires approximately 2.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Deepseek Vl2 Tiny 6bit and how large is it?

Deepseek Vl2 Tiny 6bit is developed by mlx-community, a model with 848m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Deepseek Vl2 Tiny 6bit?

Deepseek Vl2 Tiny 6bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Deepseek Vl2 Tiny 6bit by mlx-community — VRAM 2.9GB

Name: Deepseek Vl2 Tiny 6bit
Author: mlx-community

Deepseek Vl2 Tiny 6bit is an open-source language model by mlx-community. Features: 848m LLM, VRAM: 2.9GB, License: other, Quantized.

6bit Conversational Deepseek vl v2 Endpoints compatible Image-text-to-text Mlx Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mlx-community/deepseek-vl2-tiny-6bit

Deepseek Vl2 Tiny 6bit Parameters and Internals

LLM Name	Deepseek Vl2 Tiny 6bit
Repository 🤗	https://huggingface.co/mlx-community/deepseek-vl2-tiny-6bit
Model Size	848m
Required VRAM	2.9 GB
Updated	2026-08-08
Maintainer	mlx-community
Model Type	deepseek_vl_v2
Model Files	2.9 GB
Quantization Type	6bit
Model Architecture	AutoModel
License	other
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	<｜▁pad▁｜>
Torch Data Type	bfloat16

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation