Can the RTX 3080 10 GB run Qwen-Image 2.1?
Yes, but only just: Q8_0 leaves 0.1 GB free on the RTX 3080 10 GB.
Q8_0 (7.6 GB) fits with only 0.1 GB to spare (about 9.9 GB of 10 GB).
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | qwen_image_2.1_Q8_0.gguf Q8_0 · Abiray/Qwen-Image-2.1-GGUF | models/unet | 7.6 GB | Download → |
| Text encoder | qwen3vl_8b_int8_convrot.safetensors Qwen3-VL 8B INT8 · Comfy-Org/Qwen-Image-2.1 | models/text_encoders | 9.4 GB | Download → |
| VAE | qwen_image_2.1_vae_bf16.safetensors Qwen-Image 2.1 VAE · Comfy-Org/Qwen-Image-2.1 | models/vae | 0.7 GB | Download → |
| Total download · keep about the same free on disk | 17.6 GB | |||
Alternatives: Qwen3-VL 8B BF16 (17.5 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 Qwen-Image 2.1 file on 10 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 14.2 GB | 16.5 GB | 6.5 GB too big | the original weights | Hugging Face → |
| Q8_0 ← GGUF · Abiray | 7.6 GB | 9.9 GB | fits · 0.1 GB spare | practically identical to the original | Hugging Face → |
| INT8 SAFETENSORS · Comfy-Org | 7.3 GB | 9.6 GB | fits · 0.4 GB spare | practically identical to the original | Hugging Face → |
| Q6_K GGUF · Abiray | 5.9 GB | 8.2 GB | fits · 1.8 GB spare | very close to the original | Hugging Face → |
| Q5_K_M GGUF · Abiray | 5.0 GB | 7.3 GB | fits · 2.7 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · Abiray | 4.2 GB | 6.5 GB | fits · 3.5 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · Abiray | 3.2 GB | 5.5 GB | fits · 4.5 GB spare | noticeable loss of detail | Hugging Face → |
“Needed” adds 1.5 GB of working memory for Qwen-Image 2.1 and a 0.8 GB reserve. Sizes 2026-10-01.
03The text encoder
At 9.4 GB even the smallest Qwen3-VL 8B file is too big for 10 GB, so it runs from system RAM. That slows down reading the prompt, not the picture. Sizes: 16-bit 17.5 GB, INT8 9.4 GB. Why the encoder does not count against VRAM →
04Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Qwen-Image 2.1 on a RTX 3080 10 GB, send your time per image and peak VRAM and it will appear here, credited.
05About the RTX 3080 10 GB
The RTX 3080 10 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.
10 GB GDDR6X · 320-bit · 760 GB/s · Ampere. Everything that runs on it →
06Questions
How much VRAM does Qwen-Image 2.1 need?
Around 5.5 GB with the smallest file (Q3_K_M) and 9.6 GB with an 8-bit file (INT8). The full 16-bit file needs about 16.5 GB.
Which Qwen-Image 2.1 file should I download for the RTX 3080 10 GB?
Q8_0 (7.6 GB) from Abiray/Qwen-Image-2.1-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
How much do I need to download for Qwen-Image 2.1 on the RTX 3080 10 GB?
17.6 GB: qwen_image_2.1_Q8_0.gguf, qwen3vl_8b_int8_convrot.safetensors, qwen_image_2.1_vae_bf16.safetensors.