LocalClaw/LLM/GLM 4.7
Open-weight MoE

GLM 4.7

Catalogue summary: Z.ai open-weight flagship MoE with 355B total parameters and 32B active per token. The verified Q4_K_M GGUF is roughly 216.5 GB, so local use requires a 256 GB workstation class. MIT licensed.

Repository editorial metadata; verify comparative claims in the linked upstream material.

256 GB catalogue minimum256 GB RAMQ4_K_MCoding assistant
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Parameters
355B (32B active, MoE)
Minimum RAM
256 GB
Model size
216.5 GB
Quantization
Q4_K_M

Can GLM 4.7 run locally?

GLM 4.7 has a catalogue minimum of 256 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Treat glm-4.7 as a server-grade catalogue target. Use the verified artefact with a compatible multi-GPU or distributed runtime and follow its upstream instructions; this is not a one-click desktop LM Studio recommendation.

Model sourcePublic GGUF repository (verified 2026-09-07): unsloth/GLM-4.7-GGUF
chatcodepowerqualitygeneral

Deployment path

01
Check RAM fitServer-grade target. Plan for 256 GB class multi-GPU memory.
02
Load the modelUse glm-4.7 only with a compatible server-grade or distributed runtime; confirm the exact artefact and upstream instructions first.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: glm
  • Parameters: 355B (32B active, MoE)
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 256 GB
  • Catalogue model size: 216.5 GB
  • Tags: chat, code, power, quality, general

Practical limits

  • Catalogue RAM is a minimum estimate, not a guarantee for every context length or runtime.
  • Speed and memory use vary by quantization, backend, context length and system headroom.
  • Verify architecture, licence and usage restrictions in the linked upstream material before deployment.

Catalogue tags

  • chat
  • code
  • power
  • quality
  • general

Capability profile

Repository catalogue ratings used by LocalClaw's editorial rubric. They are not a standardized third-party benchmark.

speed
5
quality
9
coding
9
reasoning
9

Technical notes

Developer
See upstream repository
License
See upstream repository
Context window
See upstream repository
Architecture
See upstream repository

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

Related catalogue entries

Linked mechanically by family, shared tags and nearby RAM tier; this is not a quality ranking.

GLM-5.2 (744B MoE) 744B (40B active)GLM 4.6 (355B MoE) 355B (32B active)GLM 4.5 Air (MoE) 106B (12B active, MoE)GLM-5.3-Flash 320B (18B active, MoE)GLM-4 (32B) 32BGLM 4.7 Flash 14BGLM-4 (9B) 9BGLM-5.1 754B MoE

Where to go next