CD-GraB (WT103)
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
- Cornell University
- Organisation type
- Academia
- Country
- United States of America
- Published
- 2 February 2023
- Authors
- A. Feder Cooper, Wentao Guo, Khiem Pham, Tiancheng Yuan, Charlie F. Ruan, Yucheng Lu, Christopher De Sa
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
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.
- Parameters
- 6.8M
- Training data
- tokens
- Epochs
- 30
They provide the model initialization code in Appendix D. Running it gives the parameter count.
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
training code, Apache 2: https://github.com/GarlGuo/CD-GraB
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 9
- Benchmark data
- CD-GraB (WT103)
Sources
Where this record came from and when it was last checked.
- Reference
- CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training
- Last updated
- 11 February 2026
What the numbers mean
Where it came from
CD-GraB (WT103) was published by Cornell University, in United States of America, in February 2023. academia is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
CD-GraB (WT103) — common questions
What GPU do I need to run CD-GraB (WT103)?
None. CD-GraB (WT103) 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 CD-GraB (WT103) open source?
No. CD-GraB (WT103) has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does CD-GraB (WT103) have?
CD-GraB (WT103) has 6.8M parameters. They provide the model initialization code in Appendix D. Running it gives the parameter count. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created CD-GraB (WT103)?
CD-GraB (WT103) was published by Cornell University, based in United States of America, categorised as academia.
When was CD-GraB (WT103) released?
CD-GraB (WT103) was published in February 2023. 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 CD-GraB (WT103) used for?
CD-GraB (WT103) works in Language, and is recorded as handling language modeling. 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.
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.