Check my GPU →

Can the RTX 4060 Ti 16 GB run Qwen-Image-Edit (2511)?

Not at full quality. The 16-bit and 8-bit files are too big for the RTX 4060 Ti 16 GB; the largest that fits is Q3_K_M (9.9 GB).

Image model · 20B16 GB GDDR6 · 128-bit · 288 GB/s · Ada LovelaceData 2026-10-01
Tight
Only just.

Take Q3_K_M (9.9 GB). In use it comes to about 12.9 GB, with 3.1 GB left over on 16 GB. Quality: noticeable loss of detail. For better quality, Q4_K_M (13.2 GB) also runs, with about 0.2 GB spilling into system RAM - a little slower, still practical.

Best fileQ3_K_M
File size9.9 GB
VRAM needed~12.9 GB
System RAM32 GB+
Memory map · RTX 4060 Ti 16 GB12.9 GB / 16 GB
08 GB16 GB
Weights Q3_K_M · 9.9 GBWorking memory · 2.2 GBReserve · 0.8 GBFree · 3.1 GB

Also try the FP8 file (20.5 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
Modelqwen-image-edit-2511-Q3_K_M.gguf
Q3_K_M · unsloth/Qwen-Image-Edit-2511-GGUF
models/unet9.9 GBDownload →
Text encoderqwen_2.5_vl_7b_fp8_scaled.safetensors
Qwen2.5-VL 7B FP8 · Comfy-Org/Qwen-Image_ComfyUI
models/text_encoders9.4 GBDownload →
VAEqwen_image_vae.safetensors
Qwen-Image VAE · Comfy-Org/Qwen-Image_ComfyUI
models/vae0.3 GBDownload →
Total download · keep about the same free on disk19.6 GB

Alternatives: Qwen2.5-VL 7B BF16 (16.6 GB). Sizes from Hugging Face, 2026-10-01.

Free ComfyUI workflow, tested on my RTX 5060 Ti: GGUF Q4_K_M + 4-step LoRA workflow (.json). Drag the file into ComfyUI. All workflows →

02Every Qwen-Image-Edit file on 16 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
40.9 GB43.9 GB27.9 GB too bigthe original weightsHugging Face →
FP8
SAFETENSORS · Comfy-Org
20.5 GB23.5 GB7.5 GB too bigpractically identical to the originalHugging Face →
Q8_0
GGUF · unsloth
21.8 GB24.8 GB8.8 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · unsloth
16.9 GB19.9 GB3.9 GB too bigvery close to the originalHugging Face →
Q5_K_M
GGUF · unsloth
15.0 GB18.0 GB2.0 GB too bigclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · unsloth
13.2 GB16.2 GBspills 0.2 GBgood; some loss in fine detail and textHugging Face →
Q3_K_M ←
GGUF · unsloth
9.9 GB12.9 GBfits · 3.1 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · unsloth
7.5 GB10.5 GBfits · 5.5 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 2.2 GB of working memory for Qwen-Image-Edit 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 Qwen-Image-Edit on a RTX 4060 Ti 16 GB, send your time per image and peak VRAM and it will appear here, credited.

04With more VRAM

With 24 GB you could run Qwen-Image-Edit at 8-bit or better (FP8, 20.5 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.

05About the RTX 4060 Ti 16 GB

The RTX 4060 Ti 16 GB is an Ada Lovelace GPU with hardware FP8, so ComfyUI can compute Comfy-Org's FP8 files natively: small and fast. (Plain FP8 files use FP8 maths with the --fast fp8_matrix_mult option.)

16 GB GDDR6 · 128-bit · 288 GB/s · Ada Lovelace. Everything that runs on it →

06Questions

How much VRAM does Qwen-Image-Edit need?

Around 10.5 GB with the smallest file (Q2_K) and 23.5 GB with an 8-bit file (FP8). The full 16-bit file needs about 43.9 GB.

Which Qwen-Image-Edit file should I download for the RTX 4060 Ti 16 GB?

Q3_K_M (9.9 GB) from unsloth/Qwen-Image-Edit-2511-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

FP8 or Q8_0 for Qwen-Image-Edit on the RTX 4060 Ti 16 GB?

FP8 (20.5 GB): the RTX 4060 Ti 16 GB computes it natively, while Q8_0 (21.8 GB) is unpacked on the fly.

How much do I need to download for Qwen-Image-Edit on the RTX 4060 Ti 16 GB?

19.6 GB: qwen-image-edit-2511-Q3_K_M.gguf, qwen_2.5_vl_7b_fp8_scaled.safetensors, qwen_image_vae.safetensors.