What GPU do I need to run briaai/Fibo-2.0-edit-turbo?
8.1B parameters, published in BF16. View on Hugging FaceGated
Set up Fibo-2.0-edit-turboFibo-2.0-edit-turbo is published by briaai on Hugging Face, with 2,960 downloads and 174 likes to date. It's a unlisted-architecture model built for image-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 times a flat 1.2 overhead for activations and fragmentation. The KV-cache grows with context and is not in that factor; it is listed per model below where the architecture is published. Full formula and assumptions: methodology.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 15.1 GB | 18.2 GB | RTX 3090 | 1 | $0.162/hr |
| FP8 (quantized) | 7.6 GB | 9.1 GB | RTX 4070 | 1 | $0.154/hr |
| INT4 (quantized) | 3.8 GB | 4.5 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 Fibo-2.0-edit-turbo at its published (BF16) precision: 1× RTX 3090, at $0.162/hr per GPU ($0.162/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Fibo-2.0-edit-turbo: common questions
Does Fibo-2.0-edit-turbo fit on a 24 GB GPU?
Yes. At BF16 it needs 18.2 GB of VRAM, so a 24 GB card holds it with 5.8 GB to spare. A 16 GB card is not enough for it at BF16.
Do I need approval to download Fibo-2.0-edit-turbo?
Yes. briaai 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 18.2 GB the model needs once you have them.
What is the least VRAM Fibo-2.0-edit-turbo can run in?
4.5 GB, at INT4 (quantized), which fits a 6 GB card, against 18.2 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 Fibo-2.0-edit-turbo lower the GPU bill?
Yes. At BF16 the cheapest live fit is one RTX 3090 at $0.162/hr. At INT4 (quantized) it drops to one RTX 3060 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 briaai models
Alternatives at this size
Other models for image-to-image within about a third of Fibo-2.0-edit-turbo's 8.1B parameters, from other model lines.
- FLUX.1-Kontext-dev (11.9B, BF16)
- flux-3-image-klein (5.5B, BF16)
More on Fibo-2.0-edit-turbo
Fits on a 24 GB GPU at BF16: every model that fits in 24 GB.
Fits on a 12 GB GPU at FP8: every model that fits in 12 GB.
Fits on an 8 GB GPU at INT4: every model that fits in 8 GB.
Related reading: RTX 3090 pricing and specs, Fast diffusion inference on GPU VMs, and What AI inference is.
