Moxiaoxian
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.
- Published
- 25 January 2023
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
- 3.5B
- Training data
- tokens
"exceeds 3.5 billion"
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- 新一批国产大模型通过备案，多家垂直领域厂商入列
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Moxiaoxian was published by its authors, in January 2023.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
Moxiaoxian — common questions
What GPU do I need to run Moxiaoxian?
None. Moxiaoxian 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 Moxiaoxian open source?
The licensing for Moxiaoxian 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 Moxiaoxian have?
Moxiaoxian has 3.5B parameters. "exceeds 3.5 billion". 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.
When was Moxiaoxian released?
Moxiaoxian was published in January 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.