Table-GPT
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
- Microsoft Research
- Organisation type
- Industry
- Country
- United States of America
- Published
- 13 October 2023
- Authors
- Peng Li, Yeye He, Dror Yashar, Weiwei Cui, Song Ge, Haidong Zhang, Danielle Rifinski Fainman, Dongmei Zhang, Surajit Chaudhuri
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation, Table tasks
- Base model
- GPT-3.5 (davinci-002)
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
- 175B
- 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
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 113
Sources
Where this record came from and when it was last checked.
- Reference
- Table-GPT: Table-tuned GPT for Diverse Table Tasks
- Last updated
- 25 May 2026
What the numbers mean
What this model is
Table-GPT was published by Microsoft Research, in United States of America, in October 2023. The organisation is categorised as industry.
It works in Language, and is recorded as doing language modeling/generation, Table tasks.
It builds on GPT-3.5 (davinci-002), which is why it shares that model's general shape and size.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Table-GPT — common questions
What GPU do I need to run Table-GPT?
None. Table-GPT 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 Table-GPT open source?
No. Table-GPT has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Table-GPT have?
Table-GPT has 175B parameters. 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 Table-GPT?
Table-GPT was published by Microsoft Research, based in United States of America, categorised as industry.
When was Table-GPT released?
Table-GPT was published in October 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 Table-GPT used for?
Table-GPT works in Language, and is recorded as handling language modeling/generation, Table tasks. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
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.