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Can the RTX 3060 Ti 8 GB run FLUX.2 [klein] 4B?

Yes, but only just: Q8_0 leaves 1.9 GB free on the RTX 3060 Ti 8 GB.

Image model · 4B8 GB GDDR6 · 256-bit · 448 GB/s · AmpereData 2026-10-01
Runs well
Yes, just.

Q8_0 (4.3 GB) fits with only 1.9 GB to spare (about 6.1 GB of 8 GB).

Best fileQ8_0
File size4.3 GB
VRAM needed~6.1 GB
System RAM32 GB+
Memory map · RTX 3060 Ti 8 GB6.1 GB / 8 GB
04 GB8 GB
Weights Q8_0 · 4.3 GBWorking memory · 1.0 GBReserve · 0.8 GBFree · 1.9 GB

01What to download

PartFileFolderSize
Modelflux-2-klein-4b-Q8_0.gguf
Q8_0 · unsloth/FLUX.2-klein-4B-GGUF
models/unet4.3 GBDownload →
Text encoderqwen_3_4b_fp8_mixed.safetensors
Qwen3 4B FP8 · Comfy-Org/z_image_turbo
models/text_encoders5.6 GBDownload →
VAEflux2-vae.safetensors
FLUX.2 VAE · Comfy-Org/flux2-dev
models/vae0.3 GBDownload →
Total download · keep about the same free on disk10.3 GB

Alternatives: Qwen3 4B BF16 (8.0 GB). Sizes from Hugging Face, 2026-10-01.

Free ComfyUI workflow, tested on my RTX 5060 Ti: FP8 workflow (.json). Drag the file into ComfyUI. All workflows →

02Every FLUX.2 klein 4B file on 8 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · black-forest-labs
7.8 GB9.6 GBspills 1.6 GBthe original weightsHugging Face →
Q8_0 ←
GGUF · unsloth
4.3 GB6.1 GBfits · 1.9 GB sparepractically identical to the originalHugging Face →
FP8
SAFETENSORS · black-forest-labs
4.1 GB5.9 GBfits · 2.1 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · unsloth
3.4 GB5.2 GBfits · 2.8 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · unsloth
3.1 GB4.9 GBfits · 3.1 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · unsloth
2.6 GB4.4 GBfits · 3.6 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · unsloth
2.1 GB3.9 GBfits · 4.1 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · unsloth
1.8 GB3.6 GBfits · 4.4 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 1 GB of working memory for FLUX.2 klein 4B 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.2 klein 4B on a RTX 3060 Ti 8 GB, send your time per image and peak VRAM and it will appear here, credited.

04About 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 →

05Questions

How much VRAM does FLUX.2 klein 4B need?

Around 3.6 GB with the smallest file (Q2_K) and 5.9 GB with an 8-bit file (FP8). The full 16-bit file needs about 9.6 GB.

Which FLUX.2 klein 4B file should I download for the RTX 3060 Ti 8 GB?

Q8_0 (4.3 GB) from unsloth/FLUX.2-klein-4B-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

FP8 or Q8_0 for FLUX.2 klein 4B on the RTX 3060 Ti 8 GB?

Q8_0 (4.3 GB). The RTX 3060 Ti 8 GB has no FP8 maths, so FP8 (4.1 GB) only saves memory and is a step further from the original.

How much do I need to download for FLUX.2 klein 4B on the RTX 3060 Ti 8 GB?

10.3 GB: flux-2-klein-4b-Q8_0.gguf, qwen_3_4b_fp8_mixed.safetensors, flux2-vae.safetensors.