Hunyuan
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
- Tencent
- Organisation type
- Industry
- Country
- China
- Published
- 7 September 2023
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language, Image generation, Multimodal
- Task
- Language modeling/generation, Image generation, Question answering
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
- 100B
- Training data
- 2,000,000,000,000 tokens
"Presently, the Hunyuan model has over 100 billion parameters, with more than two trillion tokens in pre-training data."
"Presently, the Hunyuan model has over 100 billion parameters, with more than two trillion tokens in pre-training data."
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 1.2 × 10²⁴ FLOP
- How it was established
- Operation counting
6ND = 6*100*10^9*2*10^12 = 1.2*10^24
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Data centre
- There is no paper to reference, no information about hardware used for training found in media.
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
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Tencent Unveils Hunyuan, its Proprietary Large Foundation Model on Tencent Cloud
- Last updated
- 28 November 2025
What the numbers mean
What this model is
Hunyuan was published by Tencent, in the country recorded as China, during September 2023. It comes out of an organisation categorised as industry.
It works in the domain of Language, Image generation, Multimodal, and is recorded as performing the task of language modeling/generation, Image generation, Question answering.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
The training run consumed about 1.2 × 10²⁴ FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
It was trained on a corpus of about 2,000,000,000,000 tokens of text.
Answers
Hunyuan — common questions
Hunyuan— what is it used for?
It works in the domain of Language, Image generation, Multimodal, and is recorded as handling the task of language modeling/generation, Image generation, Question answering. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Hunyuan— how much compute was used to train it?
Training consumed around 1.2 × 10²⁴ FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
Hunyuan— what GPU do I need to run it?
None. This 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.
Hunyuan— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Hunyuan— how many parameters does it have?
It has a parameter count of 100B. "Presently, the Hunyuan model has over 100 billion parameters, with more than two trillion tokens in pre-training data.". 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.
Hunyuan— who created it?
It was published by Tencent, based in China, an organisation categorised as industry.
Hunyuan— when was it released?
It was published in September 2023. 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.