LocalClaw/LLM/GLM 4.6 (355B MoE)
Open-weight local LLM

GLM 4.6 (355B MoE)

Zhipu AI flagship — full GLM 4.6. 200K context, strong tool-calling & agentic workflows. Competes with Claude 3.5 Sonnet on reasoning and code. MIT licensed. Server-grade hardware.

Server-grade 320 GB RAM Q4_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
355B (32B active)
Minimum RAM
320 GB
Model size
200 GB
Quantization
Q4_K_M

Can GLM 4.6 (355B MoE) run locally?

GLM 4.6 (355B MoE) is server-grade locally. Keep it for comparison unless you have very large unified memory, multiple GPUs or remote inference.

Search for glm-4.6-355b in LM Studio or another GGUF-compatible runtime.

zai-org/GLM-4.6
chatcodereasoningqualitygeneral

Install path

01
Check RAM fitMinimum 320 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch glm-4.6-355b in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Zhipu AI flagship — full GLM 4.6. 200K context, strong tool-calling & agentic workflows. Competes with Claude 3.5 Sonnet on reasoning and code. MIT licensed. Server-grade hardware.

Limitations

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

Best use cases

  • chat
  • code
  • reasoning
  • quality
  • general

Capability profile

speed
2
quality
10
coding
10
reasoning
10

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.

Very large memoryMac Studio Ultra classCheck model size firstNVIDIA GB10 / server optionsMore practical alternativesCompare smaller models

Where to go next