feat(starter-models): add Z-Image Turbo starter models#8689
Merged
blessedcoolant merged 4 commits intoinvoke-ai:mainfrom Dec 23, 2025
Merged
feat(starter-models): add Z-Image Turbo starter models#8689blessedcoolant merged 4 commits intoinvoke-ai:mainfrom
blessedcoolant merged 4 commits intoinvoke-ai:mainfrom
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Add Z-Image Turbo and related models to the starter models list: - Z-Image Turbo (full precision, ~13GB) - Z-Image Turbo quantized (GGUF Q4_K, ~4GB) - Z-Image Qwen3 Text Encoder (full precision, ~8GB) - Z-Image Qwen3 Text Encoder quantized (GGUF Q6_K, ~3.3GB) - Z-Image ControlNet Union (Canny, HED, Depth, Pose, MLSD, Inpainting) The quantized Turbo model includes the quantized Qwen3 encoder as a dependency for automatic installation.
Pfannkuchensack
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lstein
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I suggest adding the Q6_K_M or the Q8 quant for the base model also as one of the starter models along with the new controlnet tile model. Rest seems good. Covers all VRAM bases. The rest can be manual installs. |
Add higher quality Q8_0 quantization option for Z-Image Turbo (~6.6GB) to complement existing Q4_K variant, providing better quality for users with more VRAM. Add dedicated Z-Image ControlNet Tile model (~6.7GB) for upscaling and detail enhancement workflows.
blessedcoolant
approved these changes
Dec 23, 2025
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Summary
Add Z-Image Turbo and related models to the starter models list for easy installation via the Model Manager:
The quantized Turbo model includes the quantized Qwen3 encoder as a dependency for automatic installation.
Related Issues / Discussions
Builds on the Z-Image Turbo support added in main.
QA Instructions
Merge Plan
Standard merge, no special considerations.
Checklist
What's Newcopy (if doing a release after this PR)