What GPU do I need to run briaai/Fibo-1.5?

8.3B parameters, published in BF16. View on Hugging FaceGated

Set up Fibo-1.5
8.3B
Parameters
BF16
Native precision
Unknown
Architecture
text-to-image
Pipeline

Fibo-1.5 is published by briaai on Hugging Face, with 524 downloads and 35 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in BF16, and gated: you'll need to accept the model's terms on Hugging Face before downloading weights.

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)
BF16
15.4 GB
18.5 GB
RTX 3090 (simplepod)
1
$0.160/hr
cheaper alt.
RTX 3080 (simplepod)
2
$0.140/hr
FP8 (quantized)
7.7 GB
9.3 GB
RTX 4080 (akash)
1
$0.158/hr
INT4 (quantized)
3.9 GB
4.6 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 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run Fibo-1.5 at its published (BF16) precision: 1× RTX 3090 on simplepod, at $0.160/hr per GPU ($0.160/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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