Can the RTX 3090 24 GB run Qwen-Image?
Yes, but only just: FP8 leaves 0.8 GB free on the RTX 3090 24 GB.
FP8 (20.4 GB) fits with only 0.8 GB to spare (about 23.2 GB of 24 GB).
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | qwen_image_fp8_e4m3fn.safetensors FP8 · Comfy-Org/Qwen-Image_ComfyUI | models/diffusion_models | 20.4 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 | 30.1 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 →
System RAM: 48 GB or more. These files take about 30.1 GB of RAM while loaded, 36.1 GB with Windows and ComfyUI. What happens with less. calculated
02Every Qwen-Image file on 24 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 40.9 GB | 43.7 GB | 19.7 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · city96 | 21.8 GB | 24.6 GB | spills 0.6 GB | practically identical to the original | Hugging Face → |
| FP8 ← SAFETENSORS · Comfy-Org | 20.4 GB | 23.2 GB | fits · 0.8 GB spare | practically identical to the original | Hugging Face → |
| Q6_K GGUF · city96 | 16.8 GB | 19.6 GB | fits · 4.4 GB spare | very close to the original | Hugging Face → |
| Q5_K_M GGUF · city96 | 14.9 GB | 17.7 GB | fits · 6.3 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · city96 | 13.1 GB | 15.9 GB | fits · 8.1 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · city96 | 9.7 GB | 12.5 GB | fits · 11.5 GB spare | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · city96 | 7.1 GB | 9.9 GB | fits · 14.1 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.
03Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Qwen-Image on a RTX 3090 24 GB, send your time per image and peak VRAM and it will appear here, credited.
04About the RTX 3090 24 GB
The RTX 3090 24 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.
24 GB GDDR6X · 384-bit · 936 GB/s · Ampere. Everything that runs on it →
05Questions
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 3090 24 GB?
FP8 (20.4 GB) from Comfy-Org/Qwen-Image_ComfyUI.
FP8 or Q8_0 for Qwen-Image on the RTX 3090 24 GB?
Q8_0 (21.8 GB). The RTX 3090 24 GB has no FP8 maths, so FP8 (20.4 GB) only saves memory and is a step further from the original.
How much do I need to download for Qwen-Image on the RTX 3090 24 GB?
30.1 GB: qwen_image_fp8_e4m3fn.safetensors, qwen_2.5_vl_7b_fp8_scaled.safetensors, qwen_image_vae.safetensors.