What GPU do I need to run h2oai/h2ovl-mississippi-2b?
2.2B parameters, published in BF16. View on Hugging Face
Set up h2ovl-mississippi-2bh2ovl-mississippi-2b is published by h2oai on Hugging Face, with 230,010 downloads and 44 likes to date. It's a H2OVLChatModel model built for text-generation, 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.
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 h2ovl-mississippi-2b at its published (BF16) precision: 1× RTX 3070 on simplepod, at $0.050/hr per GPU ($0.050/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
h2ovl-mississippi-2b: common questions
How much VRAM does h2ovl-mississippi-2b need?
4.8 GB at BF16, 2.4 GB at FP8 (quantized), 1.2 GB at INT4 (quantized). All of those sit under 6 GB, the smallest capacity this page reasons about, so VRAM is not what limits where this model runs. The 4.0 GB of weights plus inference overhead is the whole requirement.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
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