GPT-4.1 nano
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
- 14 April 2025
- Authors
- Research leads Ananya Kumar, Jiahui Yu, John Hallman, Michelle Pokrass Research core contributors Adam Goucher, Adi Ganesh, Bowen Cheng, Brandon McKinzie, Brian Zhang, Chris Koch, Colin Wei, David Medina, Edmund Wong, Erin Kavanaugh, Florent Bekerman, Haitang Hu, Hongyu Ren, Ishaan Singal, Jamie Kiros, Jason Ai, Ji Lin, Jonathan Chien, Josh McGrath, Julian Lee, Julie Wang, Kevin Lu, Kristian Geor…
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Multimodal, Language, Vision, Video
- Task
- Language modeling/generation, Code generation, Question answering, Quantitative reasoning, Instruction interpretation, System control, Visual question answering, Video description
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.
- 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
"GPT‑4.1 will only be available via the API"
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
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- Introducing GPT-4.1 in the API: A new series of GPT models featuring major improvements on coding, instruction following, and long context—plus our first-ever nano model.
- Last updated
- 28 November 2025
What the numbers mean
Background
GPT-4.1 nano was published by OpenAI, in United States of America, in April 2025. It comes out of industry.
It works in Multimodal, Language, Vision, Video, and is recorded as doing language modeling/generation, Code generation, Question answering, Quantitative reasoning, Instruction interpretation, System control, Visual question answering, Video description.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
GPT-4.1 nano — common questions
Who created GPT-4.1 nano?
GPT-4.1 nano was published by OpenAI, based in United States of America, categorised as industry.
When was GPT-4.1 nano released?
GPT-4.1 nano was published in April 2025.
What is GPT-4.1 nano used for?
GPT-4.1 nano works in Multimodal, Language, Vision, Video, and is recorded as handling language modeling/generation, Code generation, Question answering, Quantitative reasoning, Instruction interpretation, System control, Visual question answering, Video description. 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.
What GPU do I need to run GPT-4.1 nano?
None. GPT-4.1 nano 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-4.1 nano open source?
No. GPT-4.1 nano has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does GPT-4.1 nano have?
No parameter count has been published for GPT-4.1 nano, which is why no memory or speed figure appears on this page.
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.