GLM-5.2 744B — VRAM, Speed & Local Setup

Written by Jakub Rusinowski · Last updated August 15, 2026

Model library → GLM-5.2 → GLM-5.2 744B

The full GLM-5.2 MoE. At 744B total parameters this needs roughly 400 GB even at Q4 — a multi-node or datacenter deployment, not a workstation, despite the modest ~40B active count. Reach it through the Z.ai API or a hosted provider unless you have that hardware. The 1M-token context and MIT license are what set it apart from other models at this scale.

GLM-5.2 744B needs about 450 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters744 Billion (~40B active)
Context window1,000,000
ArchitectureMixture-of-Experts (two reasoning-effort levels)
ProviderZhipu AI (Z.ai)
LicenceMIT
Specified atQ4_K_M
System RAM768 GB
Record updated2026-08-15

Licence

MIT — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), with no KV cache (this record has no published architecture). Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantWeightsVRAM neededEst. speedFit on 24 GB
Q2_K244.6 GB245.4 GB—Won't fit
Q3_K_M317.1 GB317.9 GB—Won't fit
Q4_K_M449.2 GB450.0 GB—Won't fit
Q5_K_M527.3 GB528.1 GB—Won't fit
Q6_K610.1 GB610.9 GB—Won't fit
Q8_0790.5 GB791.3 GB—Won't fit
F161488.0 GB1488.8 GB—Won't fit

Want the memory numbers alone, at every quantization level and your own context length? Use the GLM-5.2 744B VRAM calculator.

Buy This HardwareApple Mac Studio M3 Ultra — 512 GB VRAM · 60 W board powerDeploy in the Cloud NowRunPod

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Recommended GPU

The cheapest catalogued GPU that runs GLM-5.2 744B is the Apple M3 Ultra (512 GB).

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Apple Mac Studio M3 Ultra
512 GB VRAM · 60 W board power
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How to Run GLM-5.2 744B

Install Ollama, then run:

ollama run glm-5-2

Weights on Hugging Face: zai-org/GLM-5.2.

Best for: reasoning, coding, agentic tasks, long documents, cloud api.

Can I Run GLM-5.2 744B on My GPU?

GLM-5.2 744B — Frequently Asked Questions

How much VRAM does GLM-5.2 744B need?
About 450 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does GLM-5.2 744B run on an RTX 4090 (24 GB)?
No. GLM-5.2 744B needs about 450 GB at Q4_K_M, more than a single RTX 4090's 24 GB. It needs a larger card, several GPUs, or Apple Silicon with enough unified memory — or it runs with part of the weights offloaded to system RAM, which is much slower.
How do I run GLM-5.2 744B locally?
Install Ollama and run `ollama run glm-5-2`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

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