TextImage + text

GLM (ChatGLM)

One of the oldest Chinese open lines: from ChatGLM-6B to GLM-5.3. Strong at agentic tasks and programming; GLM-5.3-Flash understands images and is released under MIT.

Developer
Zhipu AI (Z.ai), China
First release
Mar 2023
Latest release
Aug 2026
Sizes
1.5B – 744B-A40B
License
Commercial use with conditionsGLM-4.5 – GLM-5.2 and GLM-5.3-Flash: MIT; GLM-5.3: own license (API providers with revenue from $10 billion need a review by Z.ai); early ChatGLM and GLM-4-9B: own license with registration
Russian
Not supported
Ready-made builds
GGUF
Running
Available in OllamaAlso runs without a GPU
Industries
Software development, Customer support, Documents and accounting, Education
Deploy on your server Hugging Face GitHub

What it does

  • Corporate chat assistant
  • Agents for routine office tasks
  • Help for developers
  • Working with long documents

Where it is used

IT departmentCustomer supportDocument managementEducation

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
fits
ClusterServer with several GPUs — flagship versions
fits

Versions

  1. GLM-5.3 / 5.3-Flash
  2. GLM-5.2
  3. GLM-5.1
  4. GLM-5
  5. GLM-4.7-Flash 30B-A3B
  6. GLM-4.7
  7. GLM-4.5 / 4.5-Air
  8. GLM-4-32B-0414
  9. GLM-4-9B
  10. ChatGLM3-6B
  11. ChatGLM-6B

How to run it

With Ollama — the fastest wayInstall Ollama on your computer or server and find the model in its library by name. Good enough to try the model on your own tasks in one evening.Find it in the Ollama library
On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.

Frequently asked questions

Can GLM (ChatGLM) be used in a commercial project?

With conditions. License: GLM-4.5 – GLM-5.2 and GLM-5.3-Flash: MIT; GLM-5.3: own license (API providers with revenue from $10 billion need a review by Z.ai); early ChatGLM and GLM-4-9B: own license with registration. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does GLM (ChatGLM) need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does GLM (ChatGLM) support Russian?

No. The model card lists its languages and Russian is not among them.

Where can I download GLM (ChatGLM) and what does it cost?

The GLM (ChatGLM) weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

Comparisons

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Details

Source: huggingface.co/zai-org/GLM-5.3. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.