What GPU do I need to run microsoft/Phi-3-mini-128k-instruct?
3.8B parameters, published in BF16. View on Hugging Face
Set up Phi-3-mini-128k-instructPhi-3-mini-128k-instruct is published by microsoft on Hugging Face, with 286,867 downloads and 1,704 likes to date. It's a Phi3ForCausalLM 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 Phi-3-mini-128k-instruct at its published (BF16) precision: 1× RTX 3060 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.
Phi-3-mini-128k-instruct: common questions
Does Phi-3-mini-128k-instruct fit on a 12 GB GPU?
Yes. At BF16 it needs 8.5 GB of VRAM, so a 12 GB card holds it with 3.5 GB to spare. An 8 GB card is not enough for it at BF16.
What is the least VRAM Phi-3-mini-128k-instruct can run in?
2.1 GB, at INT4 (quantized), which fits a 6 GB card, against 8.5 GB at BF16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
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