feat(starter-models): add Z-Image Turbo starter models

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.

Author: Pfannkuchensack

invokeai/backend/model_manager/starter_models.py

@@ -690,6 +690,51 @@ class StarterModelBundle(BaseModel):
 )
 # endregion
 
+# region Z-Image
+z_image_qwen3_encoder = StarterModel(
+    name="Z-Image Qwen3 Text Encoder",
+    base=BaseModelType.Any,
+    source="Tongyi-MAI/Z-Image-Turbo::text_encoder",
+    description="Qwen3 4B text encoder for Z-Image (full precision). ~8GB",
+    type=ModelType.Qwen3Encoder,
+)
+
+z_image_qwen3_encoder_quantized = StarterModel(
+    name="Z-Image Qwen3 Text Encoder (quantized)",
+    base=BaseModelType.Any,
+    source="https://huggingface.co/worstplayer/Z-Image_Qwen_3_4b_text_encoder_GGUF/resolve/main/Qwen_3_4b-Q6_K.gguf",
+    description="Qwen3 4B text encoder for Z-Image quantized to GGUF Q6_K format. ~3.3GB",
+    type=ModelType.Qwen3Encoder,
+    format=ModelFormat.GGUFQuantized,
+)
+
+z_image_turbo = StarterModel(
+    name="Z-Image Turbo",
+    base=BaseModelType.ZImage,
+    source="Tongyi-MAI/Z-Image-Turbo",
+    description="Z-Image Turbo - fast 6B parameter text-to-image model with 8 inference steps. Supports bilingual prompts (English & Chinese). ~13GB",
+    type=ModelType.Main,
+)
+
+z_image_turbo_quantized = StarterModel(
+    name="Z-Image Turbo (quantized)",
+    base=BaseModelType.ZImage,
+    source="https://huggingface.co/leejet/Z-Image-Turbo-GGUF/resolve/main/z_image_turbo-Q4_K.gguf",
+    description="Z-Image Turbo quantized to GGUF Q4_K format. Requires separate Qwen3 text encoder. ~4GB",
+    type=ModelType.Main,
+    format=ModelFormat.GGUFQuantized,
+    dependencies=[z_image_qwen3_encoder_quantized],
+)
+
+z_image_controlnet_union = StarterModel(
+    name="Z-Image ControlNet Union",
+    base=BaseModelType.ZImage,
+    source="https://huggingface.co/alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1/resolve/main/Z-Image-Turbo-Fun-Controlnet-Union-2.1-8steps.safetensors",
+    description="Unified ControlNet for Z-Image Turbo supporting Canny, HED, Depth, Pose, MLSD, and Inpainting modes.",
+    type=ModelType.ControlNet,
+)
+# endregion
+
 # List of starter models, displayed on the frontend.
 # The order/sort of this list is not changed by the frontend - set it how you want it here.
 STARTER_MODELS: list[StarterModel] = [
@@ -766,6 +811,11 @@ class StarterModelBundle(BaseModel):
     cogview4,
     flux_krea,
     flux_krea_quantized,
+    z_image_turbo,
+    z_image_turbo_quantized,
+    z_image_qwen3_encoder,
+    z_image_qwen3_encoder_quantized,
+    z_image_controlnet_union,
 ]
 
 sd1_bundle: list[StarterModel] = [