aiXcoder-7B Base
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
- Peking University
- Organisation type
- Academia
- Country
- China
- Published
- 30 October 2024
- Authors
- Siyuan Jiang, Jia Li, He Zong, Huanyu Liu, Hao Zhu, Shukai Hu, Erlu Li, Jiazheng Ding, Yu Han, Wei Ning, Gen Wang, Yihong Dong, Kechi Zhang, Ge Li
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Code autocompletion
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
- 7B
- Training data
- 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 A100 SXM4 40 GB
- Chips used
- 128
- Power draw
- 100.8 kW
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
- 1
Sources
Where this record came from and when it was last checked.
- Reference
- aiXcoder-7B: A Lightweight and Effective Large Language Model for Code Completion
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
aiXcoder-7B Base was published by Peking University, in China, in October 2024. The organisation is categorised as academia.
It works in Language, and is recorded as doing code autocompletion.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
aiXcoder-7B Base — common questions
What is aiXcoder-7B Base used for?
aiXcoder-7B Base works in Language, and is recorded as handling code autocompletion. 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 aiXcoder-7B Base?
None. aiXcoder-7B Base 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 aiXcoder-7B Base open source?
The licensing for aiXcoder-7B Base 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 aiXcoder-7B Base have?
aiXcoder-7B Base has 7B 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 aiXcoder-7B Base?
aiXcoder-7B Base was published by Peking University, based in China, categorised as academia.
When was aiXcoder-7B Base released?
aiXcoder-7B Base was published in October 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.