GLM-4
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
- 17 January 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, Multimodal, Image generation
- Task
- Language modeling/generation, Question answering, Code generation, Text-to-image, Image 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.
- Training data
- 10,000,000,000,000 tokens
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
- Hosted access (no API)
- Training code
- Unreleased
GLM-4 All Tools is accessible via the website https://chatglm.cn
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
- ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
- Last updated
- 28 November 2025
What the numbers mean
Background
GLM-4 was published by Z.ai (Zhipu AI), in China, in January 2024. industry is the category the publisher falls under.
It works in Language, Multimodal, Image generation, and is recorded as doing language modeling/generation, Question answering, Code generation, Text-to-image, Image 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
The training set ran to roughly 10,000,000,000,000 tokens.
Answers
GLM-4 — common questions
Is GLM-4 open source?
No. GLM-4 has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does GLM-4 have?
No parameter count has been published for GLM-4, which is why no memory or speed figure appears on this page.
Who created GLM-4?
GLM-4 was published by Z.ai (Zhipu AI), based in China, categorised as industry.
When was GLM-4 released?
GLM-4 was published in January 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.
What is GLM-4 used for?
GLM-4 works in Language, Multimodal, Image generation, and is recorded as handling language modeling/generation, Question answering, Code generation, Text-to-image, Image generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run GLM-4?
None. GLM-4 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.
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.