What GPU do I need to run KRAFTON/A.X-K2-Raon-Speech-21B-A3B?

21.2B parameters, published in BF16. View on Hugging Face

21.2B
Parameters
BF16
Native precision
RaonModel
Architecture
any-to-any
Pipeline

A.X-K2-Raon-Speech-21B-A3B is published by KRAFTON on Hugging Face, with 19,132 downloads and 102 likes to date. It's a RaonModel model built for any-to-any, 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
39.5 GB
47.4 GB
A40 (runpod)
1
$0.440/hr
cheaper alt.
RTX 3070 (simplepod)
6
$0.300/hr
FP8 (quantized)
19.7 GB
23.7 GB
RTX 4090 (runpod)
1
$0.340/hr
cheaper alt.
RTX 4070 (simplepod)
2
$0.160/hr
INT4 (quantized)
9.9 GB
11.8 GB
RTX 3060 (simplepod)
1
$0.080/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 A.X-K2-Raon-Speech-21B-A3B at its published (BF16) precision: 1× A40 on runpod, at $0.440/hr per GPU ($0.440/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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