Can the RTX 2060 6 GB run Z-Image Turbo?
Not at full quality. The 16-bit and 8-bit files are too big for the RTX 2060 6 GB; the largest that fits is Q2_K (3.6 GB).
Q2_K (3.6 GB) fits with only 0.4 GB to spare (about 5.6 GB of 6 GB). Quality: heavy loss; a last resort. For better quality, Q3_K_M (4.2 GB) also runs, with about 0.2 GB spilling into system RAM - a little slower, still practical.
Also try the INT8 file (6.2 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
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | z-image-turbo-Q2_K.gguf Q2_K · unsloth/Z-Image-Turbo-GGUF | models/unet | 3.6 GB | Download → |
| Text encoder | qwen_3_4b_fp8_mixed.safetensors Qwen3 4B FP8 · Comfy-Org/z_image_turbo | models/text_encoders | 5.6 GB | Download → |
| VAE | ae.safetensors FLUX.1 VAE (ae) · Comfy-Org/z_image_turbo | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 9.6 GB | |||
Alternatives: Qwen3 4B BF16 (8.0 GB). Sizes from Hugging Face, 2026-10-01.
Free ComfyUI workflow, tested on my RTX 5060 Ti: 16-bit workflow (.json). Drag the file into ComfyUI. All workflows →
02Every Z-Image Turbo file on 6 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 12.3 GB | 14.3 GB | 8.3 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · unsloth | 7.2 GB | 9.2 GB | 3.2 GB too big | practically identical to the original | Hugging Face → |
| INT8 SAFETENSORS · Comfy-Org | 6.2 GB | 8.2 GB | 2.2 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · unsloth | 5.9 GB | 7.9 GB | spills 1.9 GB | very close to the original | Hugging Face → |
| Q5_K_M GGUF · unsloth | 5.6 GB | 7.6 GB | spills 1.6 GB | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · unsloth | 5.0 GB | 7.0 GB | spills 1.0 GB | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · unsloth | 4.2 GB | 6.2 GB | spills 0.2 GB | noticeable loss of detail | Hugging Face → |
| Q2_K ← GGUF · unsloth | 3.6 GB | 5.6 GB | fits · 0.4 GB spare | heavy loss; a last resort | Hugging Face → |
“Needed” adds 1.2 GB of working memory for Z-Image Turbo and a 0.8 GB reserve. Sizes 2026-10-01.
03The text encoder
At 5.6 GB even the smallest Qwen3 4B file is too big for 6 GB, so it runs from system RAM. That slows down reading the prompt, not the picture. Sizes: 16-bit 8.0 GB, FP8 5.6 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 Z-Image Turbo on a RTX 2060 6 GB, send your time per image and peak VRAM and it will appear here, credited.
05With more VRAM
With 10 GB you could run Z-Image Turbo at 8-bit or better (Q8_0, 7.2 GB) with no offloading: for example on the RTX 3080 10 GB.
What changes from the RTX 2060 6 GB to the RTX 3060 12 GB → · What changes from the RTX 2060 6 GB to the RTX 5060 Ti 16 GB →
06About the RTX 2060 6 GB
The RTX 2060 6 GB (Turing) 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.
6 GB GDDR6 · 192-bit · 336 GB/s · Turing. Everything that runs on it →
07Questions
How much VRAM does Z-Image Turbo need?
Around 5.6 GB with the smallest file (Q2_K) and 8.2 GB with an 8-bit file (INT8). The full 16-bit file needs about 14.3 GB.
Which Z-Image Turbo file should I download for the RTX 2060 6 GB?
Q2_K (3.6 GB) from unsloth/Z-Image-Turbo-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
How much do I need to download for Z-Image Turbo on the RTX 2060 6 GB?
9.6 GB: z-image-turbo-Q2_K.gguf, qwen_3_4b_fp8_mixed.safetensors, ae.safetensors.