---
title: Juggernaut Z | Runware Docs
url: https://runware.ai/docs/models/rundiffusion-juggernaut-z
description: Polished image model with stronger cinematic lighting, cleaner focus, and richer portrait detail
---
# Juggernaut Z

Juggernaut Z is a fine-tuned image model built on Z Image Base and tuned for a more presentation-ready visual style. Its strengths include more dramatic lighting, stronger camera focus, more detailed skin textures, cleaner anatomy, improved scene composition, and more coherent rendering across portraits, fashion, architecture, and cinematic concept work.

- **ID**: `rundiffusion:200@100`
- **Status**: live
- **Creator**: RunDiffusion
- **Release Date**: April 29, 2026
- **Capabilities**: Text to Image, Image to Image, Checkpoint

## Pricing

Price depends on acceleration parameter. None: $ 0.01495, Low: $0.0117, Medium: $0.01248

- **1024 x 1024**: `$ 0.01495`

## Compatibility & Validation

When `strength` or `inputs.maskImage` is provided, `inputs.seedImage` is required.

---

`width` and `height` must be used together.

## Request Parameters

**API Options**

Platform-level options for task execution and delivery.

### [taskType](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-tasktype)

- **Type**: `string`
- **Required**: true
- **Value**: `imageInference`

Identifier for the type of task being performed

### [taskUUID](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-taskuuid)

- **Type**: `string`
- **Required**: true
- **Format**: `UUID v4`

UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.

### [outputType](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-outputtype)

- **Type**: `string`
- **Default**: `URL`

Image output type.

**Allowed values**: `URL` `base64Data` `dataURI`

### [outputFormat](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-outputformat)

- **Type**: `string`
- **Default**: `JPG`

Specifies the file format of the generated output. The available values depend on the task type and the specific model's capabilities.

- \`JPG\`: Best for photorealistic images with smaller file sizes (no transparency).
- \`PNG\`: Lossless compression, supports high quality and transparency (alpha channel).
- \`WEBP\`: Modern format providing superior compression and transparency support.

> [!NOTE]
> \*\*Transparency\*\*: If you are using features like background removal or LayerDiffuse that require transparency, you must select a format that supports an alpha channel (e.g., \`PNG\`, \`WEBP\`, \`TIFF\`). \`JPG\` does not support transparency.

**Allowed values**: `JPG` `PNG` `WEBP`

### [outputQuality](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-outputquality)

- **Type**: `integer`
- **Min**: `20`
- **Max**: `99`
- **Default**: `95`

Compression quality of the output. Higher values preserve quality but increase file size.

### [webhookURL](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-webhookurl)

- **Type**: `string`
- **Format**: `URI`

Specifies a webhook URL where JSON responses will be sent via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available.

**Learn more** (1 resource):

- [Webhooks](https://runware.ai/docs/platform/webhooks) (platform)

### [deliveryMethod](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-deliverymethod)

- **Type**: `string`
- **Default**: `sync`

Determines how the API delivers task results.

**Allowed values**:

- `sync` Returns complete results directly in the API response.
- `async` Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse.

**Learn more** (1 resource):

- [Task Polling](https://runware.ai/docs/platform/task-polling) (platform)

### [uploadEndpoint](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-uploadendpoint)

- **Type**: `string`
- **Format**: `URI`

Specifies a URL where the generated content will be automatically uploaded using the HTTP PUT method. The raw binary data of the media file is sent directly as the request body. For secure uploads to cloud storage, use presigned URLs that include temporary authentication credentials.

**Common use cases:**

- **Cloud storage**: Upload directly to S3 buckets, Google Cloud Storage, or Azure Blob Storage using presigned URLs.
- **CDN integration**: Upload to content delivery networks for immediate distribution.

```text
// S3 presigned URL for secure upload
https://your-bucket.s3.amazonaws.com/generated/content.mp4?X-Amz-Signature=abc123&X-Amz-Expires=3600

// Google Cloud Storage presigned URL
https://storage.googleapis.com/your-bucket/content.jpg?X-Goog-Signature=xyz789

// Custom storage endpoint
https://storage.example.com/uploads/generated-image.jpg
```

The content data will be sent as the request body to the specified URL when generation is complete.

### [safety](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-safety)

- **Path**: `safety.checkContent`
- **Type**: `object (1 property)`

Content safety checking configuration for image generation.

#### [checkContent](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-safety-checkcontent)

- **Path**: `safety.checkContent`
- **Type**: `boolean`
- **Default**: `false`

Enable or disable content safety checking.

### [ttl](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ttl)

- **Type**: `integer`
- **Min**: `60`

Time-to-live (TTL) in seconds for generated content. Only applies when `outputType` is `URL`.

### [includeCost](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-includecost)

- **Type**: `boolean`
- **Default**: `false`

Include task cost in the response.

### [numberResults](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-numberresults)

- **Type**: `integer`
- **Min**: `1`
- **Max**: `20`
- **Default**: `1`

Number of results to generate. Each result uses a different seed, producing variations of the same parameters.

### [acceleratorOptions](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions)

- **Path**: `acceleratorOptions.cacheEndStep`
- **Type**: `object (12 properties)`

Advanced caching mechanisms to speed up generation.

#### [cacheEndStep](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-cacheendstep)

- **Path**: `acceleratorOptions.cacheEndStep`
- **Type**: `integer`
- **Min**: `1`

Absolute step number to end caching. Must be greater than `cacheStartStep` and less than or equal to `steps`.

#### [cacheEndStepPercentage](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-cacheendsteppercentage)

- **Path**: `acceleratorOptions.cacheEndStepPercentage`
- **Type**: `integer`
- **Min**: `1`
- **Max**: `100`

Percentage of steps to end caching. Alternative to `cacheEndStep`. Must be greater than `cacheStartStepPercentage`.

#### [cacheMaxConsecutiveSteps](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-cachemaxconsecutivesteps)

- **Path**: `acceleratorOptions.cacheMaxConsecutiveSteps`
- **Type**: `integer`
- **Min**: `1`
- **Max**: `5`
- **Default**: `3`

Limits the maximum number of consecutive steps that can use cached computations before forcing a fresh computation.

#### [cacheStartStep](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-cachestartstep)

- **Path**: `acceleratorOptions.cacheStartStep`
- **Type**: `integer`
- **Min**: `0`

Absolute step number to start caching. Must be less than `cacheEndStep`.

#### [cacheStartStepPercentage](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-cachestartsteppercentage)

- **Path**: `acceleratorOptions.cacheStartStepPercentage`
- **Type**: `integer`
- **Min**: `0`
- **Max**: `99`

Percentage of steps to start caching. Alternative to `cacheStartStep`. Must be less than `cacheEndStepPercentage`.

#### [fbCache](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-fbcache)

- **Path**: `acceleratorOptions.fbCache`
- **Type**: `boolean`
- **Default**: `false`

First Block Cache (FBCache) acceleration. Reuses feature block computations across steps.

#### [fbCacheThreshold](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-fbcachethreshold)

- **Path**: `acceleratorOptions.fbCacheThreshold`
- **Type**: `float`
- **Min**: `0`
- **Max**: `1`
- **Step**: `0.01`
- **Default**: `0.25`

Controls the sensitivity threshold for determining when to reuse cached computations. Lower values reuse more aggressively.

#### [teaCache](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-teacache)

- **Path**: `acceleratorOptions.teaCache`
- **Type**: `boolean`
- **Default**: `false`

TeaCache acceleration for transformer-based models. Estimates step differences to skip redundant computations.

#### [teaCacheDistance](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-teacachedistance)

- **Path**: `acceleratorOptions.teaCacheDistance`
- **Type**: `float`
- **Min**: `0`
- **Max**: `1`
- **Step**: `0.01`
- **Default**: `0.5`

Controls the aggressiveness of the TeaCache feature. Lower values prioritize quality, higher values prioritize speed.

#### [dbCache](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-dbcache)

- **Path**: `acceleratorOptions.dbCache`
- **Type**: `boolean`
- **Default**: `false`

DB Cache (CacheDiT) acceleration. Caches and reuses intermediate transformer block outputs to skip redundant computations.

#### [dbCacheThreshold](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-dbcachethreshold)

- **Path**: `acceleratorOptions.dbCacheThreshold`
- **Type**: `float`
- **Min**: `0`
- **Max**: `1`
- **Step**: `0.01`
- **Default**: `0.25`

Controls the sensitivity threshold for DB Cache. Lower values reuse cached blocks more aggressively, higher values prioritize quality.

#### [dbCacheSkipInterval](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-acceleratoroptions-dbcacheskipinterval)

- **Path**: `acceleratorOptions.dbCacheSkipInterval`
- **Type**: `integer`
- **Min**: `1`
- **Default**: `5`

Controls how many steps to skip between cache refreshes. Higher values skip more steps for faster generation at the cost of quality.

**Inputs**

Input resources for the task (images, audio, etc). These must be nested inside the \`inputs\` object.

### [seedImage](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-inputs-seedimage)

- **Path**: `inputs.seedImage`
- **Type**: `string`

Image used as a starting point for the generation (UUID, URL, Data URI, or Base64).

**Learn more** (3 resources):

- [Image To Image: Seed Image The Foundation](https://runware.ai/docs/learn/image-to-image#seed-image-the-foundation) (learn)
- [Image Inpainting: Seed And Mask Image The Foundation](https://runware.ai/docs/learn/image-inpainting#seed-and-mask-image-the-foundation) (learn)
- [Image Outpainting: Seed Image The Starting Point](https://runware.ai/docs/learn/image-outpainting#seed-image-the-starting-point) (learn)

### [maskImage](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-inputs-maskimage)

- **Path**: `inputs.maskImage`
- **Type**: `string`

Image used to specify which areas of the seed image should be edited (UUID, URL, Data URI, or Base64).

**Learn more** (1 resource):

- [Image Inpainting: Seed And Mask Image The Foundation](https://runware.ai/docs/learn/image-inpainting#seed-and-mask-image-the-foundation) (learn)

**Core Parameters**

Primary parameters that define the task output.

### [model](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-model)

- **Type**: `string`
- **Required**: true
- **Value**: `rundiffusion:200@100`

Identifier of the model to use for generation.

### [positivePrompt](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-positiveprompt)

- **Type**: `string`
- **Required**: true
- **Min**: `2`
- **Max**: `10000`

Text prompt describing elements to include in the generated output.

### [negativePrompt](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-negativeprompt)

- **Type**: `string`
- **Min**: `2`
- **Max**: `3000`

Prompt to guide what to exclude from generation. Ignored when guidance is disabled (CFGScale ≤ 1).

### [width](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-width)

- **Type**: `integer`
- **Required**: true
- **Min**: `128`
- **Max**: `2048`
- **Step**: `16`

Width of the generated media in pixels.

### [height](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-height)

- **Type**: `integer`
- **Required**: true
- **Min**: `128`
- **Max**: `2048`
- **Step**: `16`

Height of the generated media in pixels.

### [seed](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-seed)

- **Type**: `integer`
- **Min**: `0`
- **Max**: `9223372036854776000`

Random seed for reproducible generation. When not provided, a random seed is generated in the unsigned 32-bit range.

### [steps](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-steps)

- **Type**: `integer`
- **Min**: `1`
- **Max**: `50`
- **Default**: `35`

Total number of denoising steps. Higher values generally produce more detailed results but take longer.

### [scheduler](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-scheduler)

- **Type**: `string`
- **Default**: `FlowMatchEulerDiscreteScheduler`

Scheduler to use for the diffusion process.

**Allowed values**: `DDIM` `DDIMScheduler` `DDPMScheduler` `DEISMultistepScheduler` `Default` `DPM++` `DPM++ 2M` `DPM++ 2M Beta` `DPM++ 2M Exponential` `DPM++ 2M Karras` `DPM++ 2M SDE` `DPM++ 2M SDE Beta` `DPM++ 2M SDE Exponential` `DPM++ 2M SDE Karras` `DPM++ 2M SDE Uniform` `DPM++ 2M Uniform` `DPM++ 3M` `DPM++ 3M Beta` `DPM++ 3M Exponential` `DPM++ 3M Karras` `DPM++ 3M SDE Uniform` `DPM++ 3M Uniform` `DPM++ Beta` `DPM++ Exponential` `DPM++ Karras` `DPM++ SDE` `DPM++ SDE Beta` `DPM++ SDE Exponential` `DPM++ SDE Karras` `DPM++ Uniform` `DPM++ Uniform Beta` `DPM++ Uniform Exponential` `DPM++ Uniform Karras` `DPMSolverMultistepInverse` `DPMSolverMultistepScheduler` `DPMSolverSinglestepScheduler` `EDMDPMSolverMultistepScheduler` `EDMEulerScheduler` `Euler` `Euler a` `Euler Beta` `Euler DiscreteScheduler` `Euler Exponential` `Euler Karras` `EulerAncestralDiscreteScheduler` `FlowMatchEulerDiscreteScheduler` `Heun` `HeunDiscreteScheduler` `Heun Karras` `IPNDMScheduler` `IPNDM Uniform` `IPNDM Uniform Beta` `IPNDM Uniform Exponential` `IPNDM Uniform Karras` `KDPM2AncestralDiscreteScheduler` `KDPM2DiscreteScheduler` `LCM` `LCMScheduler` `LMS` `LMSDiscreteScheduler` `LMS Karras` `PNDMScheduler` `TCDScheduler` `UniPC` `UniPC 2M` `UniPC 2M Karras` `UniPC 2M Uniform` `UniPC 3M` `UniPC 3M Karras` `UniPC 3M Uniform` `UniPC Karras` `UniPC Uniform` `UniPC Uniform Beta` `UniPC Uniform Exponential` `UniPC Uniform Karras`

### [CFGScale](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-cfgscale)

- **Type**: `float`
- **Min**: `0`
- **Max**: `20`
- **Step**: `0.01`
- **Default**: `6`

Guidance scale representing how closely the output will resemble the prompt. Higher values produce results more aligned with the prompt.

### [strength](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-strength)

- **Type**: `float`
- **Min**: `0`
- **Max**: `1`
- **Step**: `0.01`
- **Default**: `0.8`

Strength of the transformation. Lower values result in more influence from the original input.

### [maskMargin](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-maskmargin)

- **Type**: `integer`
- **Min**: `32`
- **Max**: `128`

Extra context pixels around the masked region during inpainting. The model zooms into the masked area with these additional pixels for better integration.

### [outpaint](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-outpaint)

- **Type**: `object`

Pixel extensions for each boundary direction of the source image.

### [lora](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-lora)

- **Path**: `lora.model`
- **Type**: `array of objects (3 properties)`

Configuration for Low-Rank Adaptation models.

#### [model](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-lora-model)

- **Path**: `lora.model`
- **Type**: `string`
- **Required**: true

LoRA model identifier.

#### [weight](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-lora-weight)

- **Path**: `lora.weight`
- **Type**: `float`
- **Min**: `-4`
- **Max**: `4`
- **Step**: `0.01`
- **Default**: `1`

Strength of the LoRA influence. A value of 0 means no influence. Higher values increase the influence, and negative values can be used to steer away from the LoRA's style.

#### [transformer](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-lora-transformer)

- **Path**: `lora.transformer`
- **Type**: `string`
- **Default**: `both`

Transformer stages to apply LoRA. Some video models use separate high-noise and low-noise processing stages, and LoRAs can be selectively applied to optimize their effectiveness.

**Allowed values**:

- `high` Apply LoRA only to the high-noise processing stage (coarse structure and early generation steps).
- `low` Apply LoRA only to the low-noise processing stage (fine details and later generation steps).
- `both` Apply LoRA to both stages for full coverage.

### [controlNet](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet)

- **Path**: `controlNet.model`
- **Type**: `array of objects (8 properties)`

Configuration for identifying and applying ControlNet models.

#### [model](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-model)

- **Path**: `controlNet.model`
- **Type**: `string`
- **Required**: true

ControlNet model identifier.

#### [weight](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-weight)

- **Path**: `controlNet.weight`
- **Type**: `float`
- **Min**: `-4`
- **Max**: `4`
- **Step**: `0.01`
- **Default**: `1`

Strength of the ControlNet influence. A value of 0 means no influence. Higher values increase the influence, and negative values can be used to steer away from the guide image.

#### [guideImage](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-guideimage)

- **Path**: `controlNet.guideImage`
- **Type**: `string`
- **Required**: true

Reference image for ControlNet guidance (UUID, URL, Data URI, or Base64).

#### [controlMode](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-controlmode)

- **Path**: `controlNet.controlMode`
- **Type**: `string`
- **Default**: `balanced`

ControlNet guidance mode.

**Allowed values**:

- `balanced` Equal weight between ControlNet and prompt.
- `controlnet` Prioritize ControlNet guidance.
- `prompt` Prioritize prompt guidance.

#### [endStep](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-endstep)

- **Path**: `controlNet.endStep`
- **Type**: `integer`
- **Min**: `1`

Absolute step number to end ControlNet influence. Must be greater than `startStep` and less than or equal to `steps`.

#### [endStepPercentage](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-endsteppercentage)

- **Path**: `controlNet.endStepPercentage`
- **Type**: `integer`
- **Min**: `1`
- **Max**: `100`

Percentage of steps to end ControlNet influence. Must be greater than `startStepPercentage`.

#### [startStep](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-startstep)

- **Path**: `controlNet.startStep`
- **Type**: `integer`
- **Min**: `0`

Absolute step number to start ControlNet influence. Must be less than `endStep`.

#### [startStepPercentage](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-controlnet-startsteppercentage)

- **Path**: `controlNet.startStepPercentage`
- **Type**: `integer`
- **Min**: `0`
- **Max**: `99`

Percentage of steps to start ControlNet influence. Must be less than `endStepPercentage`.

**Features**

Standalone addons and post-processing features.

### [ultralytics](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics)

- **Path**: `ultralytics.CFGScale`
- **Type**: `object (9 properties)`

Configuration object for Ultralytics face enhancement during generation. This feature uses face detection and inpainting to improve facial details in the same generation step, without requiring post-processing.

> [!NOTE]
> Face enhancement is available for Stable Diffusion 1.X, SDXL, and FLUX models. The system automatically detects faces and applies targeted refinement to improve quality while maintaining consistency with the overall generation.

#### [CFGScale](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-cfgscale)

- **Path**: `ultralytics.CFGScale`
- **Type**: `float`
- **Min**: `0`
- **Max**: `50`
- **Step**: `0.1`
- **Default**: `8`

Face refinement guidance scale.

#### [confidence](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-confidence)

- **Path**: `ultralytics.confidence`
- **Type**: `float`
- **Min**: `0`
- **Max**: `1`
- **Step**: `0.01`
- **Default**: `0.9`

Confidence threshold for detection.

#### [inpaintSize](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-inpaintsize)

- **Path**: `ultralytics.inpaintSize`
- **Type**: `integer`
- **Min**: `128`
- **Max**: `2048`
- **Default**: `1024`

Image size (in pixels) to use for each inpainting region. YOLO detects faces, crops the region, and scales it to this size before running diffusion. Set so most faces land in the 2–4× range of their original pixel size. Going beyond 8× may degrade identity resemblance.

#### [maskBlur](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-maskblur)

- **Path**: `ultralytics.maskBlur`
- **Type**: `integer`
- **Min**: `0`
- **Max**: `100`
- **Default**: `5`

Mask feathering amount. Higher values create softer transitions between the enhanced face region and surrounding areas.

#### [maskPadding](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-maskpadding)

- **Path**: `ultralytics.maskPadding`
- **Type**: `integer`
- **Min**: `0`
- **Max**: `20`
- **Default**: `5`

Padding around detected face in pixels. Expands the refinement area to include surrounding context like hair and neck.

#### [negativePrompt](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-negativeprompt)

- **Path**: `ultralytics.negativePrompt`
- **Type**: `string`

Negative prompt for detection.

#### [positivePrompt](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-positiveprompt)

- **Path**: `ultralytics.positivePrompt`
- **Type**: `string`

Positive prompt for detection.

#### [steps](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-steps)

- **Path**: `ultralytics.steps`
- **Type**: `integer`
- **Min**: `1`
- **Max**: `100`
- **Default**: `20`

Number of face refinement steps.

#### [strength](https://runware.ai/docs/models/rundiffusion-juggernaut-z#request-ultralytics-strength)

- **Path**: `ultralytics.strength`
- **Type**: `float`
- **Min**: `0`
- **Max**: `1`
- **Step**: `0.01`
- **Default**: `0.3`

Refinement strength. Lower values preserve more of the original, higher values allow more aggressive reconstruction.

## Response Parameters

### [taskType](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-tasktype)

- **Type**: `string`
- **Required**: true
- **Value**: `imageInference`

Identifier for the type of task this response belongs to.

### [taskUUID](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-taskuuid)

- **Type**: `string`
- **Required**: true
- **Format**: `UUID v4`

UUID v4 identifier echoed from the original request, used to match async responses to their tasks.

### [imageUUID](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-imageuuid)

- **Type**: `string`
- **Required**: true
- **Format**: `UUID v4`

UUID of the output image.

### [imageURL](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-imageurl)

- **Type**: `string`
- **Format**: `URI`

URL of the output image.

### [imageBase64Data](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-imagebase64data)

- **Type**: `string`

Base64-encoded image data.

### [imageDataURI](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-imagedatauri)

- **Type**: `string`
- **Format**: `URI`

Data URI of the output image.

### [seed](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-seed)

- **Type**: `integer`

The seed used for generation. If none was provided, shows the randomly generated seed.

### [NSFWContent](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-nsfwcontent)

- **Type**: `boolean`

Flag indicating if NSFW content was detected.

### [cost](https://runware.ai/docs/models/rundiffusion-juggernaut-z#response-cost)

- **Type**: `float`

Task cost in USD. Present when `includeCost` is set to `true` in the request.

## Examples

### Stormglass Ballroom Desert Pageant (Text to Image)

![Stormglass Ballroom Desert Pageant]()

**Request**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "a41d7855-8047-4213-9745-1cdbcec52504",
  "model": "rundiffusion:200@100",
  "positivePrompt": "Inside a colossal glass-domed ballroom half-buried in rolling desert dunes, an avant-garde couture pageant unfolds on a reflective black stone aisle, a statuesque model wearing a sculptural gown made of mirrored shards, silk pleats, and metallic embroidery, windblown fabric, suspended dust sparkling in angled sunbeams through cracked stormglass panels, cinematic fashion editorial, dramatic high-contrast lighting, razor-sharp focus on the figure, elegant anatomy, highly detailed skin texture, luxurious materials, grand symmetrical composition, distant seated guests as soft silhouettes, warm amber and pale cyan color contrast, premium magazine photography aesthetic",
  "negativePrompt": "lowres, blurry, extra fingers, bad hands, malformed anatomy, duplicate people, crowd in foreground, flat lighting, overexposed, washed out, cartoon, painterly, text, watermark, frame, oversaturated",
  "width": 1024,
  "height": 1536,
  "seed": 57356,
  "steps": 36,
  "scheduler": "DPM++ 2M Karras",
  "CFGScale": 6.5
}
```

**Response**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "a41d7855-8047-4213-9745-1cdbcec52504",
  "imageUUID": "3b9ae453-4b4a-4890-9578-2dd36339143f",
  "imageURL": "https://im.runware.ai/image/os/a02d21/ws/3/ii/3b9ae453-4b4a-4890-9578-2dd36339143f.jpg",
  "seed": 57356,
  "cost": 0.02496
}
```

---

### Velvet Runway Understorm Atrium (Text to Image)

![Velvet Runway Understorm Atrium]()

**Request**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "d61a01d1-6bee-4e6d-913c-e0a70f66f482",
  "model": "rundiffusion:200@100",
  "positivePrompt": "high-fashion editorial scene inside a vast storm-battered atrium, a statuesque model in a sculptural deep burgundy velvet gown with intricate folded shoulders and a sweeping train, wet black marble floor reflecting soft highlights, towering fractured concrete arches, distant flashes of lightning outside massive openings, dramatic rim lighting, precise camera focus on face and fabric texture, realistic skin detail, elegant posture, clean anatomy, luxury styling, cinematic composition, subtle wind in the dress, muted palette with burgundy, charcoal, silver and pale ivory, premium magazine aesthetic, ultra-detailed, refined, sophisticated, atmospheric depth",
  "negativePrompt": "lowres, blurry, extra fingers, bad hands, deformed anatomy, duplicate person, asymmetrical eyes, oversaturated colors, flat lighting, noisy background, cropped head, cheap fabric, cartoon, illustration, text, watermark, logo",
  "width": 1024,
  "height": 1536,
  "seed": 68359,
  "steps": 36,
  "scheduler": "DPM++ 2M Karras",
  "CFGScale": 6.5
}
```

**Response**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "d61a01d1-6bee-4e6d-913c-e0a70f66f482",
  "imageUUID": "e18182a4-2f00-415d-b052-d5e9e1441217",
  "imageURL": "https://im.runware.ai/image/os/a04d20/ws/3/ii/e18182a4-2f00-415d-b052-d5e9e1441217.jpg",
  "seed": 68359,
  "cost": 0.02327
}
```

---

### Submerged Grand Piano Salon (Text to Image)

![Submerged Grand Piano Salon]()

**Request**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "a667cc90-a9ff-46a8-ad66-c528f765de4f",
  "model": "rundiffusion:200@100",
  "positivePrompt": "A surreal flooded salon inside a forgotten seaside manor, a polished black grand piano half-submerged in clear shallow water, floating sheet music, fractured crystal chandelier reflections across the ceiling, ornate plaster walls with peeling gilt trim, tall arched windows revealing a pale stormy horizon, one elegantly dressed musician seated at the piano bench with impeccable anatomy and natural skin detail, dramatic directional light, cinematic focus, crisp foreground reflections, intricate textures, refined composition, luxurious yet haunting atmosphere, ultra-detailed, presentation-ready, realistic lens rendering",
  "negativePrompt": "lowres, blurry, distorted hands, extra fingers, duplicate person, warped anatomy, poorly drawn face, oversaturated, flat lighting, cluttered composition, text, watermark, frame",
  "width": 1024,
  "height": 768,
  "seed": 61293,
  "steps": 36,
  "scheduler": "DPM++ 2M Karras",
  "CFGScale": 6.5
}
```

**Response**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "a667cc90-a9ff-46a8-ad66-c528f765de4f",
  "imageUUID": "6a3aaf44-df18-45a7-a963-4f466cf4a69f",
  "imageURL": "https://im.runware.ai/image/os/a10dlim3/ws/3/ii/6a3aaf44-df18-45a7-a963-4f466cf4a69f.jpg",
  "seed": 61293,
  "cost": 0.01326
}
```

---

### Rain-Slicked Opera Concourse (Text to Image)

![Rain-Slicked Opera Concourse]()

**Request**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "f1bfb026-3b8b-4388-8199-66b7ae56092f",
  "model": "rundiffusion:200@100",
  "positivePrompt": "A poised couture violinist standing alone in a vast contemporary opera concourse after a cloudburst, towering travertine columns, sweeping glass ceiling streaked with rain, glossy black stone floor filled with reflections, sculptural silver gown with intricate pleats and subtle metallic embroidery, violin case at her feet, distant ticket counters and curved staircases, dramatic editorial lighting, rich contrast, clean anatomy, detailed skin texture, crisp facial focus, elegant composition, cinematic atmosphere, premium fashion photography mixed with architectural visualization, ultra-detailed, refined, presentation-ready image",
  "negativePrompt": "lowres, blurry, distorted anatomy, extra fingers, duplicate person, cropped head, bad hands, warped face, flat lighting, oversaturated, noisy background, text, watermark, logo",
  "width": 1024,
  "height": 1536,
  "seed": 43931,
  "steps": 36,
  "scheduler": "DPM++ 2M Karras",
  "CFGScale": 6.5
}
```

**Response**:

```json
{
  "taskType": "imageInference",
  "taskUUID": "f1bfb026-3b8b-4388-8199-66b7ae56092f",
  "imageUUID": "a998c84e-2f2c-43a1-8baf-2f5623f503ba",
  "imageURL": "https://im.runware.ai/image/os/a04d20/ws/3/ii/a998c84e-2f2c-43a1-8baf-2f5623f503ba.jpg",
  "seed": 43931,
  "cost": 0.02418
}
```