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Can the RTX 3060 Ti 8 GB run FLUX.1 Krea [dev]?

Not at full quality. The 16-bit and 8-bit files are too big for the RTX 3060 Ti 8 GB; the largest that fits is Q3_K_M (5.4 GB).

Image model · 12B8 GB GDDR6 · 256-bit · 448 GB/s · AmpereData 2026-10-01
Tight
Only just.

Q3_K_M (5.4 GB) fits with only 0.3 GB to spare (about 7.7 GB of 8 GB). Quality: noticeable loss of detail. For better quality, Q4_K_M (6.9 GB) also runs, with about 1.2 GB spilling into system RAM - a little slower, still practical.

Best fileQ3_K_M
File size5.4 GB
VRAM needed~7.7 GB
System RAM32 GB+
Memory map · RTX 3060 Ti 8 GB7.7 GB / 8 GB
04 GB8 GB
Weights Q3_K_M · 5.4 GBWorking memory · 1.5 GBReserve · 0.8 GBFree · 0.3 GB

Also try the FP8 file (11.9 GB) on this GPU. It does not fit entirely, but a current ComfyUI streams the overflow from RAM and native 8-bit files often beat a small GGUF that does fit. Dynamic VRAM →

01What to download

PartFileFolderSize
Modelflux1-krea-dev-Q3_K_M.gguf
Q3_K_M · QuantStack/FLUX.1-Krea-dev-GGUF
models/unet5.4 GBDownload →
Text encodert5xxl_fp8_e4m3fn.safetensors
T5-XXL FP8 · comfyanonymous/flux_text_encoders
models/text_encoders4.9 GBDownload →
Text encoderclip_l.safetensors
CLIP-L · comfyanonymous/flux_text_encoders
models/text_encoders0.2 GBDownload →
VAEae.safetensors
FLUX.1 VAE (ae) · Comfy-Org/Lumina_Image_2.0_Repackaged
models/vae0.3 GBDownload →
Total download · keep about the same free on disk10.8 GB

Alternatives: T5-XXL FP16 (9.8 GB). Sizes from Hugging Face, 2026-10-01.

02Every FLUX.1 Krea file on 8 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · black-forest-labs
23.8 GB26.1 GB18.1 GB too bigthe original weightsHugging Face →
Q8_0
GGUF · QuantStack
12.7 GB15.0 GB7.0 GB too bigpractically identical to the originalHugging Face →
FP8
SAFETENSORS · Comfy-Org
11.9 GB14.2 GB6.2 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · QuantStack
9.8 GB12.1 GB4.1 GB too bigvery close to the originalHugging Face →
Q5_K_M
GGUF · QuantStack
8.4 GB10.7 GB2.7 GB too bigclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · QuantStack
6.9 GB9.2 GBspills 1.2 GBgood; some loss in fine detail and textHugging Face →
Q3_K_M ←
GGUF · QuantStack
5.4 GB7.7 GBfits · 0.3 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · QuantStack
4.0 GB6.3 GBfits · 1.7 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 1.5 GB of working memory for FLUX.1 Krea and a 0.8 GB reserve. Sizes 2026-10-01.

03Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run FLUX.1 Krea on a RTX 3060 Ti 8 GB, send your time per image and peak VRAM and it will appear here, credited.

04With more VRAM

With 16 GB you could run FLUX.1 Krea at 8-bit or better (Q8_0, 12.7 GB) with no offloading: for example on the RTX 5080 16 GB, RTX 5070 Ti 16 GB, RTX 5060 Ti 16 GB.

What changes from the RTX 3060 Ti 8 GB to the RTX 5060 Ti 16 GB →

05About the RTX 3060 Ti 8 GB

The RTX 3060 Ti 8 GB (Ampere) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain - Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.

8 GB GDDR6 · 256-bit · 448 GB/s · Ampere. Everything that runs on it →

06Questions

How much VRAM does FLUX.1 Krea need?

Around 6.3 GB with the smallest file (Q2_K) and 14.2 GB with an 8-bit file (FP8). The full 16-bit file needs about 26.1 GB.

Which FLUX.1 Krea file should I download for the RTX 3060 Ti 8 GB?

Q3_K_M (5.4 GB) from QuantStack/FLUX.1-Krea-dev-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

FP8 or Q8_0 for FLUX.1 Krea on the RTX 3060 Ti 8 GB?

Q8_0 (12.7 GB). The RTX 3060 Ti 8 GB has no FP8 maths, so FP8 (11.9 GB) only saves memory and is a step further from the original.

How much do I need to download for FLUX.1 Krea on the RTX 3060 Ti 8 GB?

10.8 GB: flux1-krea-dev-Q3_K_M.gguf, t5xxl_fp8_e4m3fn.safetensors, clip_l.safetensors, ae.safetensors.