GPT-3.5 Turbo Instruct
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
- 28 September 2023
- Authors
- John Schulman, Barret Zoph, Christina Kim, Jacob Hilton, Jacob Menick, Jiayi Weng, Juan Felipe Ceron Uribe, Liam Fedus, Luke Metz, Michael Pokorny, Rapha Gontijo Lopes, Shengjia Zhao, Arun Vijayvergiya, Eric Sigler, Adam Perelman, Chelsea Voss, Mike Heaton, Joel Parish, Dave Cummings, Rajeev Nayak, Valerie Balcom, David Schnurr, Tomer Kaftan, Chris Hallacy, Nicholas Turley, Noah Deutsch, Vik Goel,…
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation, Question answering, Chat
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
- 20B
- Training data
- tokens
20B parameters according to Table 1 in Microsoft's CODEFUSION paper: https://arxiv.org/pdf/2310.17680.pdf
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Cloud vendor
- Azure AI
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
available on API: https://platform.openai.com/docs/models/gpt-3-5-turbo
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Likely above 10²³ FLOP
- Yes
- Why it is tracked
- Historical significance,Significant use
- Record confidence
- Likely
https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/ was the default free model in ChatGPT, so likely one of the most popular models in existence
Sources
Where this record came from and when it was last checked.
- Reference
- A fast, inexpensive model for simple tasks
- Last updated
- 8 April 2026
What the numbers mean
What this model is
GPT-3.5 Turbo Instruct was published by OpenAI, in United States of America, in September 2023. industry is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling/generation, Question answering, Chat.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
It is tracked in the underlying dataset for one reason in particular: historical significance,Significant use.
Answers
GPT-3.5 Turbo Instruct — common questions
What is GPT-3.5 Turbo Instruct used for?
GPT-3.5 Turbo Instruct works in Language, and is recorded as handling language modeling/generation, Question answering, Chat. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run GPT-3.5 Turbo Instruct?
None. GPT-3.5 Turbo Instruct 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 GPT-3.5 Turbo Instruct open source?
No. GPT-3.5 Turbo Instruct has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does GPT-3.5 Turbo Instruct have?
GPT-3.5 Turbo Instruct has 20B parameters. 20B parameters according to Table 1 in Microsoft's CODEFUSION paper: https://arxiv.org/pdf/2310.17680.pdf. 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 GPT-3.5 Turbo Instruct?
GPT-3.5 Turbo Instruct was published by OpenAI, based in United States of America, categorised as industry.
When was GPT-3.5 Turbo Instruct released?
GPT-3.5 Turbo Instruct was published in September 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.
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.