What GPU do I need to run bigscience/bloom-560m?
559M parameters, published in F16. View on Hugging Face
Set up bloom-560mbloom-560m is published by bigscience on Hugging Face, with 467,931 downloads and 375 likes to date. It's a BloomForCausalLM model built for text-generation, 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 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run bloom-560m at its published (F16) precision: 1× A16 on vultr, at $0.059/hr per GPU ($0.059/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
bloom-560m: common questions
How much VRAM does bloom-560m need?
1.2 GB at FP16, 0.6 GB at FP8 (quantized), 0.3 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 1.0 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.
More bigscience models
- bloomz-560m (559M, F16)
- bloom-1b7 (1.7B, F16)
- bloom-3b (3.0B, F16)
- bloom (176.2B, BF16)
- bloom-1b1 (1.1B, F16)
- bert-base-uncased (110M, F32)
