Diplodocus
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
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
- Meta AI,Massachusetts Institute of Technology (MIT)
- Organisation type
- Industry,Academia
- Country
- United States of America
- Published
- 11 October 2022
- Authors
- Anton Bakhtin, David J Wu, Adam Lerer, Jonathan Gray, Athul Paul Jacob, Gabriele Farina, Alexander H Miller, Noam Brown
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Games
- Task
- Diplomacy
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
"we train the architecture described in Appendix F on a dataset of roughly 46000 online Diplomacy games provided by webdiplomacy.net." then self-play training
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
- Open — downloadable
- Model access
- Open weights (non-commercial)
- Training code
- Open source
creative commons (non comm) for model weights, MIT for code https://github.com/facebookresearch/diplomacy_cicero?tab=readme-ov-file#license-for-model-weights
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- SOTA improvement
- Record confidence
- Unknown
- Citations
- 65
SOTA Improvement in no-press Diplomacy "In a 200-game no-press Diplomacy tournament involving 62 human participants spanning skill levels from beginner to expert, two Diplodocus agents both achieved a higher average score than all other participants who played more than two games, and ranked first and third according to an Elo ratings model. "
Sources
Where this record came from and when it was last checked.
- Reference
- Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
Diplodocus was published by Meta AI,Massachusetts Institute of Technology (MIT), in the country recorded as United States of America, during October 2022. It comes out of an organisation categorised as industry,Academia.
It works in the domain of Games, and is recorded as performing the task of diplomacy.
Published weights mean the model runs on your machine rather than someone else's, which is what makes the hardware question below answerable at all.
What went into building it
Its inclusion criterion: sOTA improvement.
Answers
Diplodocus — common questions
Diplodocus— is it open source?
Its weights are published, so it can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
Diplodocus— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Diplodocus— who created it?
It was published by Meta AI,Massachusetts Institute of Technology (MIT), based in United States of America, an organisation categorised as industry,Academia.
Diplodocus— when was it released?
It was published in October 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.
Diplodocus— what is it used for?
It works in the domain of Games, and is recorded as handling the task of diplomacy. These are the areas it was designed around; they describe intent rather than a hard boundary.
Diplodocus— where can I download it?
The weights are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
Diplodocus— what GPU do I need to run it?
We cannot say. It has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
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.