OV-DINO
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Guangzhou AI Public Computing Center,Sun Yat-sen University,Meituan Inc,Pengcheng Lab
- Organisation type
- Government,Industry,Academia,Industry,Academia
- Country
- China
- Published
- 22 July 2024
- Authors
- Hao Wang, Pengzhen Ren, Zequn Jie, Xiao Dong, Chengjian Feng, Yinlong Qian, Lin Ma, Dongmei Jiang, Yaowei Wang, Xiangyuan Lan, Xiaodan Liang
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Object detection
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
- Epochs
- 24
batch size: 128 epochs: 24 resolution: [800, 1333]
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Open source
Apache 2.0 https://github.com/wanghao9610/OV-DINO weights are supposed to be here but the repo is empty [August 2025] https://huggingface.co/hao9610/OV-DINO
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
OV-DINO was published by Guangzhou AI Public Computing Center,Sun Yat-sen University,Meituan Inc,Pengcheng Lab, in China, in July 2024. It comes out of government,Industry,Academia,Industry,Academia.
It works in Vision, and is recorded as doing object detection.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
OV-DINO — common questions
Who created OV-DINO?
OV-DINO was published by Guangzhou AI Public Computing Center,Sun Yat-sen University,Meituan Inc,Pengcheng Lab, based in China, categorised as government,Industry,Academia,Industry,Academia.
When was OV-DINO released?
OV-DINO was published in July 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is OV-DINO used for?
OV-DINO works in Vision, and is recorded as handling object detection. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
What GPU do I need to run OV-DINO?
None. OV-DINO is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is OV-DINO open source?
No. OV-DINO has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does OV-DINO have?
No parameter count has been published for OV-DINO, which is why no memory or speed figure appears on this page.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.