LLaDA
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
- Renmin University of China,Ant Group
- Organisation type
- Academia,Industry
- Country
- China
- Published
- 14 February 2025
- Authors
- Shen Nie, Fengqi Zhu, Zebin You, Xiaolu Zhang, Jingyang Ou, Jun Hu, Jun Zhou, Yankai Lin, Ji-Rong Wen, Chongxuan Li
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Code generation, Language modeling/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.
- Parameters
- 8B
- Training data
- 2,300,000,000,000 tokens
2.3 trillion tokens
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA H800 SXM5
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.
- Training code
- Unreleased
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
- 631
Sources
Where this record came from and when it was last checked.
- Reference
- Large Language Diffusion Models
- Last updated
- 25 May 2026
What the numbers mean
Background
LLaDA was published by Renmin University of China,Ant Group, in China, in February 2025. academia,Industry is the category the publisher falls under.
It works in Language, and is recorded as doing code generation, Language modeling/generation.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
The training set ran to roughly 2,300,000,000,000 tokens.
Answers
LLaDA — common questions
Is LLaDA open source?
The licensing for LLaDA 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 LLaDA have?
LLaDA has 8B parameters. 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 LLaDA?
LLaDA was published by Renmin University of China,Ant Group, based in China, categorised as academia,Industry.
When was LLaDA released?
LLaDA was published in February 2025.
What is LLaDA used for?
LLaDA works in Language, and is recorded as handling code generation, Language modeling/generation. 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 LLaDA?
None. LLaDA 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.
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.