What GPU do I need to run black-forest-labs/FLUX.1-Krea-dev?
11.9B parameters, published in BF16. View on Hugging FaceGated
Set up FLUX.1-Krea-devFLUX.1-Krea-dev is published by black-forest-labs on Hugging Face, with 64,880 downloads and 899 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.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 22.2 GB | 26.6 GB | RTX A6000 | 1 | $0.363/hr |
| cheaper alt. | RTX 5060 Ti | 2 | $0.220/hr | ||
| FP8 (quantized) | 11.1 GB | 13.3 GB | RTX 5060 Ti | 1 | $0.110/hr |
| INT4 (quantized) | 5.5 GB | 6.7 GB | RTX 3060 | 1 | $0.110/hr |
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 FLUX.1-Krea-dev at its published (BF16) precision: 1× RTX A6000, at $0.363/hr per GPU ($0.363/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
FLUX.1-Krea-dev: common questions
Does FLUX.1-Krea-dev fit on a 32 GB GPU?
Yes. At BF16 it needs 26.6 GB of VRAM, so a 32 GB card holds it with 5.4 GB to spare. A 24 GB card is not enough for it at BF16.
Do I need approval to download FLUX.1-Krea-dev?
Yes. black-forest-labs gates this repository on Hugging Face, so you have to accept its terms with a signed-in account before the weights will download. It does not change the 26.6 GB the model needs once you have them.
What is the least VRAM FLUX.1-Krea-dev can run in?
6.7 GB, at INT4 (quantized), which fits an 8 GB card, against 26.6 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.
Does quantizing FLUX.1-Krea-dev lower the GPU bill?
Yes. At BF16 the cheapest live fit is one RTX A6000 at $0.363/hr. At FP8 (quantized) it drops to one RTX 5060 Ti at $0.110/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More FLUX.1 models
- FLUX.1-dev (11.9B, BF16)
- FLUX.1-Kontext-dev (11.9B, BF16)
- FLUX.1-schnell (11.9B, BF16)
- FLUX.1-Turbo-Alpha (347M, BF16)
Lineage
Based on FLUX.1-dev.
Alternatives at this size
Other models for text-to-image within about a third of FLUX.1-Krea-dev's 11.9B parameters, from other model lines.
- HiDream-I1-Fast (17.1B, BF16)
- Krea-2-Turbo (12.8B, BF16)
- stable-diffusion-3.5-large (8.1B, BF16)
- Chroma1-HD (8.9B, BF16)
- FIBO (8.3B, BF16)
More on FLUX.1-Krea-dev
Fits on a 32 GB GPU at BF16: every model that fits in 32 GB.
Fits on a 16 GB GPU at FP8: every model that fits in 16 GB.
Fits on an 8 GB GPU at INT4: every model that fits in 8 GB.
Best image generation models: how FLUX.1-Krea-dev ranks against the rest.
Compare FLUX.1-Krea-dev with stable-diffusion-v1-4, sd-turbo, Qwen-Image.
Related reading: RTX A6000 pricing and specs, Fast diffusion inference on GPU VMs, and What AI inference is.
