What GPU do I need to run ATH-MaaS/Ovis2-4B?

4.6B parameters, published in BF16. View on Hugging Face

4.6B
Parameters
BF16
Native precision
Ovis
Architecture
image-text-to-text
Pipeline

Ovis2-4B is published by ATH-MaaS on Hugging Face, with 13,310 downloads and 63 likes to date. It's a Ovis model built for image-text-to-text, 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
8.6 GB
10.3 GB
RTX 4070 (simplepod)
1
$0.080/hr
FP8 (quantized)
4.3 GB
5.2 GB
RTX 4070 (simplepod)
1
$0.080/hr
INT4 (quantized)
2.1 GB
2.6 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 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run Ovis2-4B at its published (BF16) precision: 1× RTX 4070 on simplepod, at $0.080/hr per GPU ($0.080/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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