Can the RTX 4060 Ti 8 GB run Qwen-Image?
Not entirely. Even Q2_K is 1.9 GB over 8 GB, so ComfyUI keeps part of it in system RAM.
Nothing fits entirely, but Q2_K (7.1 GB) overflows by only about 1.9 GB. ComfyUI keeps that part in system RAM automatically: slower than a full fit, but usable.
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 →
01With more VRAM
With 24 GB you could run Qwen-Image at 8-bit or better (FP8, 20.4 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.
What changes from the RTX 4060 Ti 8 GB to the RTX 5060 Ti 16 GB →
02Every Qwen-Image file on 8 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 40.9 GB | 43.7 GB | 35.7 GB too big | the original weights | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 20.4 GB | 23.2 GB | 15.2 GB too big | practically identical to the original | Hugging Face → |
| Q8_0 GGUF · city96 | 21.8 GB | 24.6 GB | 16.6 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · city96 | 16.8 GB | 19.6 GB | 11.6 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · city96 | 14.9 GB | 17.7 GB | 9.7 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · city96 | 13.1 GB | 15.9 GB | 7.9 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · city96 | 9.7 GB | 12.5 GB | 4.5 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K ← GGUF · city96 | 7.1 GB | 9.9 GB | spills 1.9 GB | 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.
03What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | qwen-image-Q2_K.gguf Q2_K · city96/Qwen-Image-gguf | models/unet | 7.1 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 | 16.7 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 →
04The text encoder
At 9.4 GB even the smallest Qwen2.5-VL 7B file is too big for 8 GB, so it runs from system RAM. That slows down reading the prompt, not the picture. Sizes: 16-bit 16.6 GB, FP8 9.4 GB. Why the encoder does not count against VRAM →
05Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Qwen-Image on a RTX 4060 Ti 8 GB, send your time per image and peak VRAM and it will appear here, credited.
06About the RTX 4060 Ti 8 GB
The RTX 4060 Ti 8 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.)
8 GB GDDR6 · 128-bit · 288 GB/s · Ada Lovelace. Everything that runs on it →
07Questions
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 4060 Ti 8 GB?
Q2_K (7.1 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 4060 Ti 8 GB?
FP8 (20.4 GB): the RTX 4060 Ti 8 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 4060 Ti 8 GB?
16.7 GB: qwen-image-Q2_K.gguf, qwen_2.5_vl_7b_fp8_scaled.safetensors, qwen_image_vae.safetensors.