Can the RTX 5060 Ti 16 GB run Qwen-Image?
Timed on my own card, not estimated: 123.3 seconds per 1024x1024 image with the Q4_K_M file, peaking at 15.7 GB.
Q4_K_M (13.1 GB) fits with only 0.1 GB to spare (about 15.9 GB of 16 GB). Quality: good; some loss in fine detail and text. For better quality, Q5_K_M (14.9 GB) also runs, with about 1.7 GB spilling into system RAM - a little slower, still practical.
Also try the FP8 file (20.4 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 →
01My measurements
| Label | Setup | Result | Peak VRAM | Date | Source |
|---|---|---|---|---|---|
| measured | qwen-image-Q4_K_M.gguf · 1024x1024 · 20 steps 20 steps, CFG 2.5, euler/simple, ModelSamplingAuraFlow 3.1. Text encoder Qwen2.5-VL 7B FP8 (scaled), Qwen-Image VAE. 3 timed runs after 1 warm-up (138.7 s incl. loading). VRAM was | 123.32 s / image | 15.7 GB | 2026-10-12 |
02What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | qwen-image-Q4_K_M.gguf Q4_K_M · city96/Qwen-Image-gguf | models/unet | 13.1 GB | Download → |
| Text encoder | qwen_2.5_vl_7b_fp8_scaled.safetensors Qwen2.5-VL 7B FP8 · Comfy-Org/Qwen-Image_ComfyUI | models/text_encoders | 9.4 GB | Download → |
| VAE | qwen_image_vae.safetensors Qwen-Image VAE · Comfy-Org/Qwen-Image_ComfyUI | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 22.7 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 workflow (.json). Drag the file into ComfyUI. All workflows →
03Every Qwen-Image file on 16 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 40.9 GB | 43.7 GB | 27.7 GB too big | the original weights | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 20.4 GB | 23.2 GB | 7.2 GB too big | practically identical to the original | Hugging Face → |
| Q8_0 GGUF · city96 | 21.8 GB | 24.6 GB | 8.6 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · city96 | 16.8 GB | 19.6 GB | 3.6 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · city96 | 14.9 GB | 17.7 GB | spills 1.7 GB | close; small differences in fine detail | Hugging Face → |
| Q4_K_M ← GGUF · city96 | 13.1 GB | 15.9 GB | fits · 0.1 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · city96 | 9.7 GB | 12.5 GB | fits · 3.5 GB spare | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · city96 | 7.1 GB | 9.9 GB | fits · 6.1 GB spare | heavy loss; a last resort | Hugging Face → |
“Needed” adds 2 GB of working memory for Qwen-Image and a 0.8 GB reserve. Sizes 2026-10-01.
04Questions
How much VRAM does Qwen-Image need?
Around 9.9 GB with the smallest file (Q2_K) and 23.2 GB with an 8-bit file (FP8). The full 16-bit file needs about 43.7 GB.
Which Qwen-Image file should I download for the RTX 5060 Ti 16 GB?
Q4_K_M (13.1 GB) from city96/Qwen-Image-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for Qwen-Image on the RTX 5060 Ti 16 GB?
FP8 (20.4 GB): the RTX 5060 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 on the RTX 5060 Ti 16 GB?
22.7 GB: qwen-image-Q4_K_M.gguf, qwen_2.5_vl_7b_fp8_scaled.safetensors, qwen_image_vae.safetensors.