docs(z-image) add Z-Image requirements and starter bundle

docs/installation/quick_start.md

@@ -31,6 +31,12 @@ Hardware requirements vary significantly depending on model and image output siz
         - Memory: At least 32GB RAM.
         - Disk: 10GB for base installation plus 200GB for models.
 
+    === "Z-Image Turbo - 1024x1024"
+        - GPU: Nvidia 20xx series or later, 8GB+ VRAM for the Q4_K quantized model. 16GB+ needed for the Q8 or BF16 models.
+        - Memory: At least 16GB RAM.
+        - Disk: 10GB for base installation plus 35GB for models.
+
+
 More detail on system requirements can be found [here](./requirements.md).
 
 ## Step 2: Download and Set Up the Launcher

docs/installation/requirements.md

@@ -31,6 +31,11 @@ The requirements below are rough guidelines for best performance. GPUs with less
         - Memory: At least 32GB RAM.
         - Disk: 10GB for base installation plus 200GB for models.
 
+    === "Z-Image Turbo - 1024x1024"
+        - GPU: Nvidia 20xx series or later, 8GB+ VRAM for the Q4_K quantized model. 16GB+ needed for the Q8 or BF16 models.
+        - Memory: At least 16GB RAM.
+        - Disk: 10GB for base installation plus 35GB for models.
+
 !!! info "`tmpfs` on Linux"
 
     If your temporary directory is mounted as a `tmpfs`, ensure it has sufficient space.

invokeai/backend/model_manager/load/load_default.py

@@ -75,6 +75,7 @@ def _load_and_cache(self, config: AnyModelConfig, submodel_type: Optional[SubMod
 
         config.path = str(self._get_model_path(config))
         self._ram_cache.make_room(self.get_size_fs(config, Path(config.path), submodel_type))
+        self._logger.info(f"Loading model '{stats_name}' into RAM cache..., config={config}")
         loaded_model = self._load_model(config, submodel_type)
 
         self._ram_cache.put(

invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py

@@ -140,6 +140,7 @@ def _load_from_singlefile(
         # Some weights of the model checkpoint were not used when initializing CLIPTextModelWithProjection:
         # ['text_model.embeddings.position_ids']
 
+        self._logger.info(f"Loading model from single file at {config.path} using {load_class.__name__}")
         with SilenceWarnings():
             pipeline = load_class.from_single_file(config.path, torch_dtype=self._torch_dtype)
 

invokeai/backend/model_manager/starter_models.py

@@ -720,20 +720,20 @@ class StarterModelBundle(BaseModel):
     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",
+    description="Z-Image Turbo quantized to GGUF Q4_K format. Requires standalone Qwen3 text encoder and Flux VAE. ~4GB",
     type=ModelType.Main,
     format=ModelFormat.GGUFQuantized,
-    dependencies=[z_image_qwen3_encoder_quantized],
+    dependencies=[z_image_qwen3_encoder_quantized, flux_vae],
 )
 
 z_image_turbo_q8 = StarterModel(
     name="Z-Image Turbo (Q8)",
     base=BaseModelType.ZImage,
     source="https://huggingface.co/leejet/Z-Image-Turbo-GGUF/resolve/main/z_image_turbo-Q8_0.gguf",
-    description="Z-Image Turbo quantized to GGUF Q8_0 format. Higher quality, larger size. Requires separate Qwen3 text encoder. ~6.6GB",
+    description="Z-Image Turbo quantized to GGUF Q8_0 format. Higher quality, larger size. Requires standalone Qwen3 text encoder and Flux VAE. ~6.6GB",
     type=ModelType.Main,
     format=ModelFormat.GGUFQuantized,
-    dependencies=[z_image_qwen3_encoder_quantized],
+    dependencies=[z_image_qwen3_encoder_quantized, flux_vae],
 )
 
 z_image_controlnet_union = StarterModel(
@@ -890,10 +890,19 @@ class StarterModelBundle(BaseModel):
     flux_krea_quantized,
 ]
 
+zimage_bundle: list[StarterModel] = [
+    z_image_turbo_quantized,
+    z_image_qwen3_encoder_quantized,
+    z_image_controlnet_union,
+    z_image_controlnet_tile,
+    flux_vae,
+]
+
 STARTER_BUNDLES: dict[str, StarterModelBundle] = {
     BaseModelType.StableDiffusion1: StarterModelBundle(name="Stable Diffusion 1.5", models=sd1_bundle),
     BaseModelType.StableDiffusionXL: StarterModelBundle(name="SDXL", models=sdxl_bundle),
     BaseModelType.Flux: StarterModelBundle(name="FLUX.1 dev", models=flux_bundle),
+    BaseModelType.ZImage: StarterModelBundle(name="Z-Image Turbo", models=zimage_bundle),
 }
 
 assert len(STARTER_MODELS) == len({m.source for m in STARTER_MODELS}), "Duplicate starter models"

invokeai/frontend/web/public/locales/en.json

@@ -1049,10 +1049,10 @@
         "t5Encoder": "T5 Encoder",
         "qwen3Encoder": "Qwen3 Encoder",
         "zImageVae": "VAE (optional)",
-        "zImageVaePlaceholder": "From Qwen3 Source (leave empty)",
+        "zImageVaePlaceholder": "From VAE source model",
         "zImageQwen3Encoder": "Qwen3 Encoder (optional)",
-        "zImageQwen3EncoderPlaceholder": "From Qwen3 Source (leave empty)",
-        "zImageQwen3Source": "Qwen3 Source (Diffusers Z-Image)",
+        "zImageQwen3EncoderPlaceholder": "From Qwen3 source model",
+        "zImageQwen3Source": "Qwen3 & VAE Source Model",
         "zImageQwen3SourcePlaceholder": "Required if VAE/Encoder empty",
         "upcastAttention": "Upcast Attention",
         "uploadImage": "Upload Image",

invokeai/frontend/web/src/features/modelManagerV2/subpanels/InstallModels.tsx

@@ -1,11 +1,11 @@
 import type { SystemStyleObject } from '@invoke-ai/ui-library';
-import { Box, Button, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs, Text } from '@invoke-ai/ui-library';
+import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
 import { useStore } from '@nanostores/react';
 import { $installModelsTabIndex } from 'features/modelManagerV2/store/installModelsStore';
 import { StarterModelsForm } from 'features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsForm';
-import { memo, useCallback } from 'react';
+import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
-import { PiCubeBold, PiFolderOpenBold, PiInfoBold, PiLinkSimpleBold, PiShootingStarBold } from 'react-icons/pi';
+import { PiCubeBold, PiFolderOpenBold, PiLinkSimpleBold, PiShootingStarBold } from 'react-icons/pi';
 import { SiHuggingface } from 'react-icons/si';
 
 import { HuggingFaceForm } from './AddModelPanel/HuggingFaceFolder/HuggingFaceForm';
@@ -24,17 +24,21 @@ export const InstallModels = memo(() => {
   const { t } = useTranslation();
   const tabIndex = useStore($installModelsTabIndex);
 
-  const onClickLearnMore = useCallback(() => {
-    window.open('https://support.invoke.ai/support/solutions/articles/151000170961-supported-models');
-  }, []);
+  {
+    /* TO DO: This click target points to an out-of-date invokeai.ai URL. Reinstate when there is an updated web link. */
+  }
+  // const onClickLearnMore = useCallback(() => {
+  //   window.open('https://support.invoke.ai/support/solutions/articles/151000170961-supported-models');
+  // }, []);
 
   return (
     <Flex layerStyle="first" borderRadius="base" w="full" h="full" flexDir="column" gap={4}>
       <Flex alignItems="center" justifyContent="space-between">
         <Heading fontSize="xl">{t('modelManager.addModel')}</Heading>
-        <Button alignItems="center" variant="link" leftIcon={<PiInfoBold />} onClick={onClickLearnMore}>
+        {/* TO DO: This button points to an out-of-date invokeai.ai URL. Reinstate when there is an updated web link. */}
+        {/* <Button alignItems="center" variant="link" leftIcon={<PiInfoBold />} onClick={onClickLearnMore}>
           <Text variant="subtext">{t('modelManager.learnMoreAboutSupportedModels')}</Text>
-        </Button>
+        </Button> */}
       </Flex>
       <Tabs
         variant="line"