What GPU do I need to run microsoft/Florence-2-large?
777M parameters, published in F16. View on Hugging Face
Florence-2-large is published by microsoft on Hugging Face, with 642,352 downloads and 1,853 likes to date. It's a Florence2ForConditionalGeneration model built for image-text-to-text, published natively in F16.
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 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run Florence-2-large at its published (F16) precision: 1× P4 on akash, at $0.032/hr per GPU ($0.032/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.
More microsoft models
- Florence-2-base (232M, F16)
- phi-2 (2.8B, F16)
- VibeVoice-ASR (8.7B, BF16)
- Phi-3.5-vision-instruct (4.1B, BF16)
- phi-4 (14.7B, BF16)
- Phi-3-mini-4k-instruct (3.8B, BF16)
