What GPU do I need to run naver-hyperclovax/HyperCLOVAX-SEED-Think-14B?

14.7B parameters, published in F32. View on Hugging Face

14.7B
Parameters
F32
Native precision
HyperCLOVAXForCausalLM
Architecture
text-generation
Pipeline

HyperCLOVAX-SEED-Think-14B is published by naver-hyperclovax on Hugging Face, with 31,244 downloads and 119 likes to date. It's a HyperCLOVAXForCausalLM model built for text-generation, published natively in F32.

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)
FP32
54.9 GB
65.9 GB
A100 (runpod)
1
$1.19/hr
cheaper alt.
P40 (akash)
3
$0.410/hr
FP8 (quantized)
13.7 GB
16.5 GB
RTX 4090 (runpod)
1
$0.340/hr
cheaper alt.
RTX 4070 (simplepod)
2
$0.160/hr
INT4 (quantized)
6.9 GB
8.2 GB
RTX 3080 (simplepod)
1
$0.070/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.

Cheapest way to run HyperCLOVAX-SEED-Think-14B at its published (F32) precision: 1× A100 on runpod, at $1.19/hr per GPU ($1.19/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

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

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