What GPU do I need to run zai-org/GLM-5.3?

753.3B parameters, published in F8_E4M3. View on Hugging Face

753.3B
Parameters
F8_E4M3
Native precision
GlmMoeDsaForCausalLM
Architecture
text-generation
Pipeline

GLM-5.3 is published by zai-org on Hugging Face, with 94,403 downloads and 1,440 likes to date. It's a GlmMoeDsaForCausalLM model built for text-generation, published natively in F8_E4M3.

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)
FP8 (native)
701.6 GB
841.9 GB
No capable live offer found
INT4 (quantized)
350.8 GB
421.0 GB
A100 (runpod)
6
$7.14/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.

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