InstructGPT 175B
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 175B (davinci)
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
- 16,969,897 tokens
"We train three model sizes (1.3B, 6B, and 175B parameters)"
Table 6 - describes **number of prompts** 26584 + 6623 = 33207 This is added to GPT-3 dataset size.
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 3.2 × 10²³ FLOP
- How it was established
- Reported
- Fine-tuning compute
- 5.2 × 10²¹ FLOP
"training our 175B PPO-ptx model requires 60 petaflops/s-days, compared to 3,640 petaflops/s-days for GPT-3 (Brown et al., 2020)" 60/3640 = +1.65% to base model compute base model was reported 3.14e+23 FLOP 3.14e+23 * 1.0165 = 319181000000000000000000
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
- Likely above 10²³ FLOP
- 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
Background
InstructGPT 175B was published by OpenAI, in the country recorded as United States of America, during January 2022. It comes out of an organisation categorised as industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation.
Its starting point was an existing base model, GPT-3 175B (davinci). That is the usual way a specialised model is produced.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
Training it took a computation budget of roughly 3.2 × 10²³ FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
The training set ran to roughly 16,969,897 tokens of text.
Its inclusion criterion: historical significance,Highly cited.
Answers
InstructGPT 175B — common questions
InstructGPT 175B— what GPU do I need to run it?
None. This 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.
InstructGPT 175B— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
InstructGPT 175B— how many parameters does it have?
It has a parameter count of 175B. "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.
InstructGPT 175B— who created it?
It was published by OpenAI, based in United States of America, an organisation categorised as industry.
InstructGPT 175B— when was it released?
It 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.
InstructGPT 175B— what is it used for?
It works in the domain of Language, and is recorded as handling the task of 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.
InstructGPT 175B— how much compute was used to train it?
Training consumed around 3.2 × 10²³ FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
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.