What GPU do I need to run alimama-creative/FLUX.1-Turbo-Alpha?
347M parameters, published in BF16. View on Hugging Face
Set up FLUX.1-Turbo-AlphaFLUX.1-Turbo-Alpha is published by alimama-creative on Hugging Face, with 14,124 downloads and 642 likes to date. It's a unlisted-architecture model built for text-to-image, published natively in BF16.
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 | 0.6 GB | 0.8 GB | RTX 5060 Ti | 1 | $0.110/hr |
| FP8 (quantized) | 0.3 GB | 0.4 GB | RTX 5060 Ti | 1 | $0.110/hr |
| INT4 (quantized) | 0.2 GB | 0.2 GB | RTX 5060 Ti | 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-Turbo-Alpha at its published (BF16) precision: 1× RTX 5060 Ti, at $0.110/hr per GPU ($0.110/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-Turbo-Alpha: common questions
How much VRAM does FLUX.1-Turbo-Alpha need?
0.8 GB at BF16, 0.4 GB at FP8 (quantized), 0.2 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 0.6 GB of weights plus inference overhead is the whole requirement.
How many copies of FLUX.1-Turbo-Alpha fit on one RTX 5060 Ti?
20, by VRAM alone. That card carries 16.0 GB and one copy needs 0.8 GB at BF16, on a live rate of $0.110/hr for the whole card. Throughput is not modelled here, so 20 copies is not 20 times the requests served.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More FLUX.1 models
- FLUX.1-schnell (11.9B, BF16)
- FLUX.1-dev (11.9B, BF16)
- FLUX.1-Kontext-dev (11.9B, BF16)
- FLUX.1-Krea-dev (11.9B, BF16)
Related reading: H100 pricing and specs, The best GPUs for AI, ranked, and Best GPU for LLM inference.
