Agent Q
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
- Stanford University
- Organisation type
- Academia
- Country
- United States of America
- Published
- 13 August 2024
- Authors
- Pranav Putta, Edmund Mills, Naman Garg, Sumeet Motwani, Chelsea Finn, Divyansh Garg, Rafael Rafailov
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Other
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
- 70B
- Training data
- tokens
For OpenTable experiments, we use the LLaMA-3-70B-Instruct model as the initial policy
600 successful trajectories used for RFT, OpenTable
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 187
Sources
Where this record came from and when it was last checked.
- Reference
- Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
- Last updated
- 25 May 2026
What the numbers mean
Background
Agent Q was published by Stanford University, in United States of America, in August 2024. academia is the category the publisher falls under.
It works in Other.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
Agent Q — common questions
What is Agent Q used for?
Agent Q works in Other. 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 Agent Q?
None. Agent Q 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 Agent Q open source?
The licensing for Agent Q was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Agent Q have?
Agent Q has 70B parameters. For OpenTable experiments, we use the LLaMA-3-70B-Instruct model as the initial policy. 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 Agent Q?
Agent Q was published by Stanford University, based in United States of America, categorised as academia.
When was Agent Q released?
Agent Q was published in August 2024. 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.