What GPU do I need to run black-forest-labs/FLUX.1-schnell?
11.9B parameters, published in BF16. View on Hugging FaceGated
FLUX.1-schnell is published by black-forest-labs on Hugging Face, with 509,255 downloads and 5,591 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in BF16, and gated — you'll need to accept the model's terms on Hugging Face before downloading weights.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for activation memory and allocator fragmentation. Diffusion and video models carry no KV-cache — the real driver of extra memory is output resolution and frame count, which this flat overhead does not model. 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 FLUX.1-schnell at its published (BF16) precision: 1× A40 on runpod, at $0.440/hr per GPU ($0.440/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 black-forest-labs models
- FLUX.1-dev (11.9B, BF16)
- FLUX.2-klein-4B (3.9B, BF16)
- FLUX.2-klein-base-4B (3.9B, BF16)
- FLUX.1-Krea-dev (11.9B, BF16)
- Qwen3-0.6B (752M, BF16)
- Qwen3-8B (8.2B, BF16)
