o3-mini
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
- 31 January 2025
- Authors
- Training Brian Zhang, Eric Mitchell, Hongyu Ren, Kevin Lu, Max Schwarzer, Michelle Pokrass, Shengjia Zhao, Ted Sanders Eval Adam Kalai, Alex Tachard Passos, Ben Sokolowsky, Elaine Ya Le, Erik Ritter, Hao Sheng, Hanson Wang, Ilya Kostrikov, James Lee, Johannes Ferstad, Michael Lampe, Prashanth Radhakrishnan, Sean Fitzgerald, Sebastien Bubeck, Yann Dubois, Yu Bai Frontier Evals & Preparedness Andy…
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, Quantitative reasoning, Code generation
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
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
- Significant use
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- Pushing the frontier of cost-effective reasoning.
- Last updated
- 10 February 2026
What the numbers mean
About this model
o3-mini was published by OpenAI, in United States of America, in January 2025. It comes out of industry.
It works in Language, and is recorded as doing language modeling/generation, Question answering, Quantitative reasoning, Code generation.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Training and provenance
It is tracked in the underlying dataset for one reason in particular: significant use.
Answers
o3-mini — common questions
What GPU do I need to run o3-mini?
None. o3-mini 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 o3-mini open source?
No. o3-mini has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does o3-mini have?
No parameter count has been published for o3-mini, which is why no memory or speed figure appears on this page.
Who created o3-mini?
o3-mini was published by OpenAI, based in United States of America, categorised as industry.
When was o3-mini released?
o3-mini was published in January 2025.
What is o3-mini used for?
o3-mini works in Language, and is recorded as handling language modeling/generation, Question answering, Quantitative reasoning, Code generation. 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.