What GPU do I need to run zai-org/GLM-5.3-BF16?

753.3B parameters, published in BF16. View on Hugging Face

Set up GLM-5.3-BF16
753.3B
Parameters
BF16
Native precision
GlmMoeDsaForCausalLM
Architecture
text-generation
Pipeline

GLM-5.3-BF16 is published by zai-org on Hugging Face, with 4,111 downloads and 30 likes to date. It's a GlmMoeDsaForCausalLM 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
1403.2 GB
1683.8 GB
No capable live offer found
FP8 (quantized)
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 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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