What GPU do I need to run zai-org/GLM-4.5?

358.3B parameters, published in BF16. View on Hugging Face

358.3B
Parameters
BF16
Native precision
Glm4MoeForCausalLM
Architecture
text-generation
Pipeline

GLM-4.5 is published by zai-org on Hugging Face, with 114,639 downloads and 1,410 likes to date. It's a Glm4MoeForCausalLM model built for text-generation, published natively in BF16.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.

Precision
Weight size
Required VRAM
Cheapest live fit
GPUs needed
Est. $/hr (full fit)
BF16
667.5 GB
800.9 GB
No capable live offer found
FP8 (quantized)
333.7 GB
400.5 GB
5
$5.80/hr
INT4 (quantized)
166.9 GB
200.2 GB
A40 (runpod)
5
$2.20/hr

A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.

INT4 caveat: requires a quantized checkpoint actually published for this model — check its Hugging Face page before relying on this row.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

More zai-org models

Ready when you are

Stop paying for
idle GPUs.

Sign up in 60 seconds. Pay only for the GPU minutes you actually use.

© 2026 Aquanode. All rights reserved.

All trademarks, logos and brand names are the property of their respective owners.