ControlNet (SD 3.5 Large) Depth
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
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
- Stability AI
- Organisation type
- Industry
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 26 November 2024
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Image generation
- Task
- Image-to-image, Image generation
- Base model
- Stable Diffusion 3.5 Large
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
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
- Open — downloadable
- Model access
- Open weights (restricted use)
- Training code
- Unreleased
- Hugging Face
- stabilityai
Stability AI Community license https://huggingface.co/stabilityai/stable-diffusion-3.5-large-controlnet-depth https://github.com/Stability-AI/sd3.5/
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
- ControlNets for Stable Diffusion 3.5 Large
- Last updated
- 11 February 2026
What the numbers mean
Background
ControlNet (SD 3.5 Large) Depth was published by Stability AI, in the country recorded as United Kingdom of Great Britain and Northern Ireland, during November 2024. The publishing organisation is categorised as industry.
It works in the domain of Image generation, and is recorded as performing the task of image-to-image, Image generation.
Rather than being trained from scratch, it is derived from Stable Diffusion 3.5 Large. Most models at this scale are adapted from an existing base rather than built from nothing.
The weights are published, so it can be downloaded and run on your own hardware indefinitely, offline, with no account attached. On Hugging Face it is published under the organisation stabilityai.
Answers
ControlNet (SD 3.5 Large) Depth — common questions
ControlNet (SD 3.5 Large) Depth— when was it released?
It was published in November 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.
ControlNet (SD 3.5 Large) Depth— what is it used for?
It works in the domain of Image generation, and is recorded as handling the task of image-to-image, Image generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
ControlNet (SD 3.5 Large) Depth— where can I download it?
Its weights are published on Hugging Face, under the organisation stabilityai. We do not host model files — this site calculates what hardware is needed to run them.
ControlNet (SD 3.5 Large) Depth— what GPU do I need to run it?
We cannot say. It has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
ControlNet (SD 3.5 Large) Depth— is it open source?
Its weights are published, so it can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
ControlNet (SD 3.5 Large) Depth— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
ControlNet (SD 3.5 Large) Depth— who created it?
It was published by Stability AI, based in United Kingdom of Great Britain and Northern Ireland, an organisation categorised as industry.
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.