InstructGPT 1.3B

Closed weights OpenAI 1.3B parameters January 2022

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
OpenAI
Organisation type
Industry
Country
United States of America
Published
27 January 2022
Authors
Long Ouyang, Pamela Mishkin, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, John Schulman, Amanda Askell, Fraser Kelton, Peter Welinder, Luke Miller, Maddie Simens, Paul Christiano, Ryan Lowe, Chong Zhang, Jacob Hilton, Sandhini Agarwal, Katarina Slama, Alex Ray, Jan Leike

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Language
Task
Language modeling/generation
Approach
Self-supervised learning
Base model
GPT-3 XL

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
1.3B

"We train three model sizes (1.3B, 6B, and 175B parameters)"

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
API access
Training code
Unreleased

used to be accessible via API, now deprecated

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Foundation model
Yes
Why it is tracked
Historical significance,Highly cited
Record confidence
Confident
Citations
20,786

Sources

Where this record came from and when it was last checked.

Reference
Training language models to follow instructions with human feedback
Last updated
25 May 2026

What the numbers mean

Where it came from

InstructGPT 1.3B was published by OpenAI, in United States of America, in January 2022. The organisation is categorised as industry.

It works in Language, and is recorded as doing language modeling/generation.

Its starting point was GPT-3 XL — most models at this scale are adapted from an existing base rather than built from nothing.

This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.

What went into building it

Its inclusion criterion is historical significance,Highly cited.

Answers

InstructGPT 1.3B — common questions

01

What is InstructGPT 1.3B used for?

InstructGPT 1.3B works in Language, and is recorded as handling language modeling/generation. 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.

02

What GPU do I need to run InstructGPT 1.3B?

None. InstructGPT 1.3B 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.

03

Is InstructGPT 1.3B open source?

No. InstructGPT 1.3B has not had its weights published, so it exists only as a service controlled by its owner.

04

How many parameters does InstructGPT 1.3B have?

InstructGPT 1.3B has 1.3B parameters. "We train three model sizes (1.3B, 6B, and 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.

05

Who created InstructGPT 1.3B?

InstructGPT 1.3B was published by OpenAI, based in United States of America, categorised as industry.

06

When was InstructGPT 1.3B released?

InstructGPT 1.3B was published in January 2022. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

Source

Original publication

Record last updated 25 May 2026

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.