CPM-2
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
- Tsinghua University,Beijing Academy of Artificial Intelligence / BAAI
- Organisation type
- Academia,Academia
- Country
- China
- Published
- 24 June 2021
- Authors
- Zhengyan Zhang, Yuxian Gu, Xu Han, Shengqi Chen, Chaojun Xiao, Zhenbo Sun, Yuan Yao, Fanchao Qi, Jian Guan, Pei Ke, Yanzheng Cai, Guoyang Zeng, Zhixing Tan, Zhiyuan Liu, Minlie Huang, Wentao Han, Yang Liu, Xiaoyan Zhu, Maosong Sun
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language 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
- 11B
- Training data
- 69,615,000,000 tokens
"we pretrain two models: an encoder-decoder bilingual model with 11 billion parameters (CPM2) and its corresponding MoE version with 198 billion parameters. "
"We pre-train our model on WuDaoCorpus (Yuan et al., 2021), which contains 2.3TB cleaned Chinese data as well as 300GB cleaned English data." 2300GB * 167M tokens/GB + 300GB * 267M tokens/GB = 464 billion tokens https://docs.google.com/document/d/1G3vvQkn4x_W71MKg0GmHVtzfd9m0y3_Ofcoew0v902Q/edit#heading=h.ieihc08p8dn0
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
- 3.6 × 10²² FLOP
- How it was established
- Operation counting
epoch count not stated C = 6 FLOP * 11B * 464B =
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
- Citations
- 101
Sources
Where this record came from and when it was last checked.
- Reference
- CPM-2: Large-scale Cost-effective Pre-trained Language Models
- Last updated
- 25 May 2026
What the numbers mean
Where it came from
CPM-2 was published by Tsinghua University,Beijing Academy of Artificial Intelligence / BAAI, in the country recorded as China, during June 2021. The category the publisher falls under is academia,Academia.
It works in the domain of Language, and is recorded as performing the task of language generation.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
What went into building it
Training it took a computation budget of roughly 3.6 × 10²² FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
Training consumed a corpus of around 69,615,000,000 tokens of text.
Answers
CPM-2 — common questions
CPM-2— when was it released?
It was published in June 2021. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
CPM-2— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language generation. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
CPM-2— how much compute was used to train it?
Training consumed around 3.6 × 10²² 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.
CPM-2— 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.
CPM-2— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
CPM-2— how many parameters does it have?
It has a parameter count of 11B. "we pretrain two models: an encoder-decoder bilingual model with 11 billion parameters (CPM2) and its corresponding MoE version with 198 billion 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.
CPM-2— who created it?
It was published by Tsinghua University,Beijing Academy of Artificial Intelligence / BAAI, based in China, an organisation categorised as academia,Academia.
The other direction
Looking at it from the other side?
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