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Can the RTX 5080 16 GB run Krea 2 (Turbo)?

Yes, but only just: FP8 leaves 0.3 GB free on the RTX 5080 16 GB.

Image model · 12.8B16 GB GDDR7 · 256-bit · 960 GB/s · BlackwellData 2026-10-01
Runs well
Yes, just.

FP8 (13.1 GB) fits with only 0.3 GB to spare (about 15.7 GB of 16 GB).

Best fileFP8
File size13.1 GB
VRAM needed~15.7 GB
System RAM32 GB+
Memory map · RTX 5080 16 GB15.7 GB / 16 GB
08 GB16 GB
Weights FP8 · 13.1 GBWorking memory · 1.8 GBReserve · 0.8 GBFree · 0.3 GB

01What to download

PartFileFolderSize
Modelkrea2_turbo_fp8_scaled.safetensors
FP8 · Comfy-Org/Krea-2
models/diffusion_models13.1 GBDownload →
Text encoderqwen3vl_4b_fp8_scaled.safetensors
Qwen3-VL 4B FP8 · Comfy-Org/Krea-2
models/text_encoders5.2 GBDownload →
VAEqwen_image_vae.safetensors
Qwen-Image VAE · Comfy-Org/Krea-2
models/vae0.3 GBDownload →
Total download · keep about the same free on disk18.6 GB

Alternatives: Qwen3-VL 4B BF16 (8.9 GB). Sizes from Hugging Face, 2026-10-01.

Free ComfyUI workflow, tested on my RTX 5060 Ti: INT8 workflow (.json). Drag the file into ComfyUI. All workflows →

02Every Krea 2 file on 16 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
26.3 GB28.9 GB12.9 GB too bigthe original weightsHugging Face →
FP8 ←
SAFETENSORS · Comfy-Org
13.1 GB15.7 GBfits · 0.3 GB sparepractically identical to the originalHugging Face →
INT8
SAFETENSORS · Comfy-Org
13.5 GB16.1 GBspills 0.1 GBpractically identical to the originalHugging Face →
Q8_0
GGUF · vantagewithai
13.7 GB16.3 GBspills 0.3 GBpractically identical to the originalHugging Face →
Q6_K
GGUF · vantagewithai
10.6 GB13.2 GBfits · 2.8 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · vantagewithai
8.9 GB11.5 GBfits · 4.5 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · vantagewithai
7.5 GB10.1 GBfits · 5.9 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · vantagewithai
6.0 GB8.6 GBfits · 7.4 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · vantagewithai
4.9 GB7.5 GBfits · 8.5 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 1.8 GB of working memory for Krea 2 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 Krea 2 on a RTX 5080 16 GB, send your time per image and peak VRAM and it will appear here, credited.

04About the RTX 5080 16 GB

The RTX 5080 16 GB is a Blackwell GPU with FP8 and FP4 hardware: ComfyUI computes Comfy-Org's FP8 files natively here, and NVFP4 files (where a model offers them) are faster still.

16 GB GDDR7 · 256-bit · 960 GB/s · Blackwell. Everything that runs on it →

05Questions

How much VRAM does Krea 2 need?

Around 7.5 GB with the smallest file (Q2_K) and 15.7 GB with an 8-bit file (FP8). The full 16-bit file needs about 28.9 GB.

Which Krea 2 file should I download for the RTX 5080 16 GB?

FP8 (13.1 GB) from Comfy-Org/Krea-2.

FP8 or Q8_0 for Krea 2 on the RTX 5080 16 GB?

FP8 (13.1 GB): the RTX 5080 16 GB computes it natively, while Q8_0 (13.7 GB) is unpacked on the fly.

How much do I need to download for Krea 2 on the RTX 5080 16 GB?

18.6 GB: krea2_turbo_fp8_scaled.safetensors, qwen3vl_4b_fp8_scaled.safetensors, qwen_image_vae.safetensors.