Open-weight local LLM

GLM-4 (32B)

Flagship GLM-4. Much better than QwQ 32B for general tasks. Llama-70B class performance at half the size. Exceptional bilingual (CN/EN).

32 GB power user 32 GB RAM Q4_K_M Coding assistant
Parameters
32B
Minimum RAM
32 GB
Model size
20 GB
Quantization
Q4_K_M

Can GLM-4 (32B) run locally?

GLM-4 (32B) belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for glm-4-32b-chat in LM Studio or another GGUF-compatible runtime.

chatcodepowerqualitygeneral

Install path

01
Check RAM fitMinimum 32 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch glm-4-32b-chat in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Flagship GLM-4. Much better than QwQ 32B for general tasks. Llama-70B class performance at half the size. Exceptional bilingual (CN/EN).

Limitations

  • Performance depends on quantization, RAM bandwidth and runtime support.

Best use cases

  • chat
  • code
  • power
  • quality
  • general

Capability profile

speed
4
quality
9
coding
9
reasoning
9

Technical notes

Developer
glm
License
See model repository
Context window
Unknown tokens
Architecture
See model card

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Where to go next