§01·compatibility · /check
Z-Image Turbo on RTX 3090
Yes — Z-Image Turbo runs on the RTX 3090 (24 GB). Fastest community-measured result: 9 s, with 13 GB peak VRAM.
✓ runsimageactive30 series24GB VRAM
§02·benchmarks
| Task | Quant | Speed | VRAM | Works | Confidence | Source | Verified |
|---|---|---|---|---|---|---|---|
| text-to-image | bf16 | 9s | 13GB | ✓ | miroleon.github.io· community-benchmark-sibling | 2026-05-27 |
§03·common questions
Can you run Z-Image Turbo on RTX 3090?
Yes — Z-Image Turbo runs on the RTX 3090 (24 GB). Fastest community-measured result: 9 s, with 13 GB peak VRAM.
How much VRAM does Z-Image Turbo need on RTX 3090?
Measured peak VRAM is 13 GB — about 11 GB of headroom on the 24 GB card.
Which quantizations have been tested for Z-Image Turbo on RTX 3090?
bf16 — measured in community benchmarks.
How fast is Z-Image Turbo on RTX 3090?
Up to 9 s (text-to-image), the fastest community-measured result.
Are there step-by-step instructions for Z-Image Turbo on RTX 3090?
Yes — a step-by-step recipe documents Z-Image Turbo on the RTX 3090; see the recipes listed below.
§04·related recipes
- imagebeginner16GB+
Z-Image Turbo on RTX 3090: 8-Step 1024x1024 Text-to-Image at BF16 with Diffusers or ComfyUI
- imagebeginner6GB+
Z-Image Turbo on Apple M2 Pro: 8-step 1024x1024 text-to-image in 16 GB unified memory with mflux
- imagebeginner17GB+
Z-Image Turbo on Apple M3 Max: 8-step 1024x1024 text-to-image in unified memory with mflux
- imagebeginner17GB+
Z-Image Turbo on Apple M4 Max: 8-step 1024x1024 text-to-image in unified memory with mflux
- imagebeginner17GB+
Z-Image Turbo on Apple M2 Max: 8-step 1024x1024 text-to-image in unified memory with mflux