What GPU do I need to run UnfilteredAI/NSFW-GEN-ANIME-v2?

2.6B parameters, published in F32. View on Hugging Face

2.6B
Parameters
F32
Native precision
Unknown
Architecture
text-to-image
Pipeline

NSFW-GEN-ANIME-v2 is published by UnfilteredAI on Hugging Face, with 21,948 downloads and 57 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in F32.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for activation memory and allocator fragmentation. Diffusion and video models carry no KV-cache — the real driver of extra memory is output resolution and frame count, which this flat overhead does not model. Full formula and assumptions: methodology.

Precision
Weight size
Required VRAM
Cheapest live fit
GPUs needed
Est. $/hr (full fit)
FP32
9.6 GB
11.5 GB
V100 (simplepod)
1
$0.060/hr
FP8 (quantized)
2.4 GB
2.9 GB
RTX 4070 Super (simplepod)
1
$0.090/hr
INT4 (quantized)
1.2 GB
1.4 GB
RTX 3070 (simplepod)
1
$0.050/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 NSFW-GEN-ANIME-v2 at its published (F32) precision: 1× V100 on simplepod, at $0.060/hr per GPU ($0.060/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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