GLM-4 (0520)
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
- Z.ai (Zhipu AI)
- Organisation type
- Industry
- Country
- China
- Published
- 20 May 2024
- Authors
- Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Diego Rojas, Guanyu Feng, Hanlin Zhao, Hanyu Lai, Hao Yu, Hongning Wang, Jiadai Sun, Jiajie Zhang, Jiale Cheng, Jiayi Gui, Jie Tang, Jing Zhang, Juanzi Li, Lei Zhao, Lindong Wu, Lucen Zhong, Mingdao Liu, Minlie Huang, Peng Zhang, Qinkai Zheng, Rui Lu, Shuaiqi Duan, Shudan Zhang, Shulin Cao, Shuxun Yang, Weng Lam Tam, Wenyi Zhao, Xiao Liu, Xiao…
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation, Question answering, Code generation, Quantitative reasoning, Translation
- Base model
- GLM-4 (0116)
- Numerical format
- BF16
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.
- Training data
- 10,000,000,000,000 tokens
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.
- How it was established
- Operation counting
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
the GLM-4 API at https://bigmodel.cn repo with models from the same series but not exactly this one: https://github.com/THUDM/GLM-4
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
- Why it is tracked
- Training cost
- Record confidence
- Likely
Trained on 10T tokens with similar architecture to GPT-4, probably >$1M compute cost.
Sources
Where this record came from and when it was last checked.
- Reference
- ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
- Last updated
- 11 February 2026
What the numbers mean
About this model
GLM-4 (0520) was published by Z.ai (Zhipu AI), in the country recorded as China, during May 2024. It comes out of an organisation categorised as industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation, Question answering, Code generation, Quantitative reasoning, Translation.
It builds on GLM-4 (0116). That is why it shares the base model's general shape and size.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
The training set ran to roughly 10,000,000,000,000 tokens of text.
It is tracked in the underlying dataset for one reason in particular: training cost.
Answers
GLM-4 (0520) — common questions
GLM-4 (0520)— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling/generation, Question answering, Code generation, Quantitative reasoning, Translation. These are the areas it was designed around; they describe intent rather than a hard boundary.
GLM-4 (0520)— 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.
GLM-4 (0520)— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
GLM-4 (0520)— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
GLM-4 (0520)— who created it?
It was published by Z.ai (Zhipu AI), based in China, an organisation categorised as industry.
GLM-4 (0520)— when was it released?
It was published in May 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.