GLM-5 744B — VRAM, Speed & Local Setup

作者： Jakub Rusinowski · 最后更新： 2026年2月15日

Model library → GLM-5 / GLM-5.1 → GLM-5 744B

Frontier MoE model with 744B total and 40B active parameters. Scores 77.8% on SWE-bench Verified and holds the highest open-source Chatbot Arena Elo at 1451. Trained on Huawei Ascend hardware — no NVIDIA dependency. Requires ~400+ GB VRAM at Q4; accessible via API at ~$0.80/1M input tokens.

GLM-5 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 window200,000
ArchitectureMixture-of-Experts + DeepSeek Sparse Attention
ProviderZhipu AI (Z.ai)
LicenceMIT
Specified atQ4_K_M
System RAM1024 GB
Record updated2026-02-15

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 744B VRAM calculator.

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

or compare on Vast.ai

As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.

Recommended GPU

The cheapest catalogued GPU that runs GLM-5 744B is the Apple M3 Ultra (512 GB).

联盟营销声明: 本页部分链接为联盟推广链接——如果你通过它们购买，LLM Configurator 可能会获得佣金，而你无需支付任何额外费用。作为亚马逊联盟成员（Amazon Associate），LLM Configurator 会从符合条件的购买中获得收益。
Apple Mac Studio M3 Ultra
512 GB VRAM · 60 W board power
2026年价格波动较大——请以当前商品页价格为准。
在亚马逊查看价格

How to Run GLM-5 744B

Install Ollama, then run:

ollama run glm-5

Weights on Hugging Face: THUDM/GLM-5.

Published Benchmark Scores

Quality scores as published by the model's authors or an independent evaluator — not throughput, and not measured by us.

BenchmarkScoreProvenance
SWE-bench Verified77.8 / 100 %reported

Best for: software engineering, coding, enterprise, cloud api.

Can I Run GLM-5 744B on My GPU?

Other GLM-5 / GLM-5.1 Sizes

GLM-5 744B — Frequently Asked Questions

How much VRAM does GLM-5 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 744B run on an RTX 4090 (24 GB)?
No. GLM-5 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 744B locally?
Install Ollama and run `ollama run glm-5`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does GLM-5 / GLM-5.1 come in?
GLM-5 9B (6 GB), GLM-5 32B (20 GB), GLM-5.1 72B (44 GB), GLM-5 744B (450 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

← All GLM-5 / GLM-5.1 models | VRAM calculator | Check your own hardware