HiDream-I1 Full
HiDream-I1 Full is a 17B parameter text to image model for high quality generation. It targets sharp detail and strong prompt alignment. It supports LoRA workflows and heavy customization. Ideal for production pipelines that need consistent visuals and open source licensing.
API Options
Platform-level options for task execution and delivery.
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taskType
string required value: imageInference -
Identifier for the type of task being performed
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taskUUID
string required UUID v4 -
UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.
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outputType
string default: URL -
Image output type.
Allowed values 3 values
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outputFormat
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.
**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 3 values
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outputQuality
integer min: 20 max: 99 default: 95 -
Compression quality of the output. Higher values preserve quality but increase file size.
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webhookURL
string 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 PLATFORM
- Webhooks
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deliveryMethod
string default: sync -
Determines how the API delivers task results.
Allowed values 2 values
- Returns complete results directly in the API response.
- Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse.
Learn more 1 resource
- Task Polling PLATFORM
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uploadEndpoint
string 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.
// 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.jpgThe content data will be sent as the request body to the specified URL when generation is complete.
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safety
object -
Content safety checking configuration for image generation.
Properties 2 properties
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safety»checkContentcheckContent
boolean default: false -
Enable or disable content safety checking. When enabled, defaults to
fastmode.
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safety»modemode
string default: none -
Safety checking mode for image generation.
Allowed values 2 values
- Disables checking.
- Performs a single check.
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ttl
integer min: 60 -
Time-to-live (TTL) in seconds for generated content. Only applies when
outputTypeisURL.
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includeCost
boolean default: false -
Include task cost in the response.
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numberResults
integer min: 1 max: 20 default: 1 -
Number of results to generate. Each result uses a different seed, producing variations of the same parameters.
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acceleratorOptions
object -
Advanced caching mechanisms to speed up generation.
Properties 12 properties
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acceleratorOptions»cacheEndStepcacheEndStep
integer min: 1 -
Absolute step number to end caching. Must be greater than
cacheStartStepand less than or equal tosteps.
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acceleratorOptions»cacheEndStepPercentagecacheEndStepPercentage
integer min: 1 max: 100 -
Percentage of steps to end caching. Alternative to
cacheEndStep. Must be greater thancacheStartStepPercentage.
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acceleratorOptions»cacheMaxConsecutiveStepscacheMaxConsecutiveSteps
integer min: 1 max: 5 default: 3 -
Limits the maximum number of consecutive steps that can use cached computations before forcing a fresh computation.
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acceleratorOptions»cacheStartStepcacheStartStep
integer min: 0 -
Absolute step number to start caching. Must be less than
cacheEndStep.
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acceleratorOptions»cacheStartStepPercentagecacheStartStepPercentage
integer min: 0 max: 99 -
Percentage of steps to start caching. Alternative to
cacheStartStep. Must be less thancacheEndStepPercentage.
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acceleratorOptions»fbCachefbCache
boolean default: false -
First Block Cache (FBCache) acceleration. Reuses feature block computations across steps.
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acceleratorOptions»fbCacheThresholdfbCacheThreshold
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.
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acceleratorOptions»teaCacheteaCache
boolean default: false -
TeaCache acceleration for transformer-based models. Estimates step differences to skip redundant computations.
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acceleratorOptions»teaCacheDistanceteaCacheDistance
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.
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acceleratorOptions»dbCachedbCache
boolean default: false -
DB Cache (CacheDiT) acceleration. Caches and reuses intermediate transformer block outputs to skip redundant computations.
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acceleratorOptions»dbCacheThresholddbCacheThreshold
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.
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acceleratorOptions»dbCacheSkipIntervaldbCacheSkipInterval
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.
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Generation Parameters
Core parameters for controlling the generated content.
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model
string required value: runware:97@1 -
Identifier of the model to use for generation.
Learn more 3 resources
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positivePrompt
string required -
Text prompt describing elements to include in the generated output.
Learn more 2 resources
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negativePrompt
string -
Prompt to guide what to exclude from generation. Ignored when guidance is disabled (CFGScale ≤ 1).
Learn more 1 resource
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width
integer min: 128 max: 2048 step: 16 default: 1024 -
Width of the generated media in pixels.
Learn more 2 resources
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height
integer min: 128 max: 2048 step: 16 default: 1024 -
Height of the generated media in pixels.
Learn more 2 resources
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seed
integer min: 0 max: 9223372036854776000 -
Random seed for reproducible generation. When not provided, a random seed is generated in the unsigned 32-bit range.
Learn more 1 resource
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steps
integer min: 1 default: 30 -
Total number of denoising steps. Higher values generally produce more detailed results but take longer.
Learn more 1 resource
-
scheduler
string -
Scheduler to use for the diffusion process.
Allowed values 75 values
Learn more 2 resources
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CFGScale
float min: 0 step: 0.01 -
Guidance scale representing how closely the output will resemble the prompt. Higher values produce results more aligned with the prompt.
Learn more 1 resource
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lora
array of objects min items: 1 -
With LoRA (Low-Rank Adaptation), you can adapt a model to specific styles or features by emphasizing particular aspects of the data. This technique enhances the quality and relevance of generated content and can be especially useful when the output needs to adhere to a specific artistic style or follow particular guidelines.
Multiple LoRA models can be used simultaneously to achieve different adaptation goals.
Examples 1 example
"lora": [ { "model": "<lora-model-air>", "weight": 0.8 } ]Learn more 1 resource
Properties 3 properties
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lora»modelmodel
string required -
LoRA model identifier.
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lora»weightweight
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.
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lora»transformertransformer
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 3 values
- Apply LoRA only to the high-noise processing stage (coarse structure and early generation steps).
- Apply LoRA only to the low-noise processing stage (fine details and later generation steps).
- Apply LoRA to both stages for full coverage.
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Submerged Cathedral Reef Procession
{
"taskType": "imageInference",
"taskUUID": "c02c8676-a2cb-4b12-8e53-09cc6cd14f84",
"model": "runware:97@1",
"positivePrompt": "An immense ancient cathedral submerged beneath a clear tropical sea, coral-encrusted arches and broken stained glass windows filtering shafts of turquoise light, a solemn procession of pearl-divers in embroidered ceremonial suits carrying luminous shell lanterns through the nave, schools of silver fish weaving between stone columns, a giant sea turtle gliding above the central aisle, tiled mosaic floor partly buried in drifting sand, ornate relics wrapped in sea vines, cinematic depth, ultra-sharp details, rich textures, atmospheric perspective, majestic and reverent mood, painterly realism, highly detailed faces and fabrics, intricate reef growth, natural color harmony",
"width": 1024,
"height": 1536,
"seed": 95341,
"steps": 30
}{
"taskType": "imageInference",
"taskUUID": "c02c8676-a2cb-4b12-8e53-09cc6cd14f84",
"imageUUID": "303872a5-fc13-4f6b-8cfb-8f2823c01560",
"imageURL": "https://im.runware.ai/image/os/a22d05/ws/2/ii/303872a5-fc13-4f6b-8cfb-8f2823c01560.jpg",
"seed": 95341,
"cost": 0.0083
}Clockwork Orchard Harvest Festival
{
"taskType": "imageInference",
"taskUUID": "ee731c2c-f21b-4193-9d55-a68c219e268f",
"model": "runware:97@1",
"positivePrompt": "A grand harvest celebration in a vast orchard of brass-and-wood fruit trees, each branch fitted with tiny gears, pulleys, copper leaves, and glass pears glowing with warm amber cores. In the center, villagers and inventors in patchwork festival attire gather around rolling apple-sorting contraptions and wind-up ladders, while children chase tiny mechanical birds between baskets of oversized apricots and polished quinces. Overhead, banners of dyed linen stretch between trees, fluttering above suspended lanterns made from carved gourds and enamel clock parts. In the distance, terraced hills hold more orchards and small milling sheds with turning wheels and smoking chimneys. Golden late-afternoon sunlight, crisp atmosphere, rich textures, highly detailed materials, precise mechanical design, lively crowd staging, cinematic depth, vibrant earthy palette, sharp focus, premium illustration quality.",
"width": 1024,
"height": 768,
"seed": 64095,
"steps": 30
}{
"taskType": "imageInference",
"taskUUID": "ee731c2c-f21b-4193-9d55-a68c219e268f",
"imageUUID": "d9b8b66a-6c0a-4d75-8696-b94834b9d8b6",
"imageURL": "https://im.runware.ai/image/os/a10d08/ws/2/ii/d9b8b66a-6c0a-4d75-8696-b94834b9d8b6.jpg",
"seed": 64095,
"cost": 0.0083
}Volcanic Glasswright Caravan Encampment
{
"taskType": "imageInference",
"taskUUID": "623e400e-cc1d-461f-a7aa-3e1992bea0fa",
"model": "runware:97@1",
"positivePrompt": "A sprawling desert encampment of traveling glasswrights at the edge of a black volcanic plain, dozens of elegant wagons with folded silk awnings arranged in a crescent, master artisans shaping molten glass with long tools beside portable furnaces, translucent sculptures cooling on wooden racks, pack animals draped in patterned textiles, wind-carved basalt spires in the distance, pale dawn sky with streaks of apricot and silver, heat shimmer over dark stone, intricate props everywhere: baskets of colored minerals, brass tongs, blown glass lanterns, cracked ceramic water jars, footprints in ash, cinematic wide shot, highly detailed, crisp focus, rich textures, realistic lighting, atmospheric depth, exceptional material contrast between glowing glass, rough basalt, woven fabric, and brushed metal",
"width": 1024,
"height": 768,
"seed": 41485,
"steps": 30
}{
"taskType": "imageInference",
"taskUUID": "623e400e-cc1d-461f-a7aa-3e1992bea0fa",
"imageUUID": "8b51b1d6-9b8f-4822-8beb-26b58da6b6d0",
"imageURL": "https://im.runware.ai/image/os/a18d05/ws/2/ii/8b51b1d6-9b8f-4822-8beb-26b58da6b6d0.jpg",
"seed": 41485,
"cost": 0.0083
}Glass Canopy Monorail Terminus
{
"taskType": "imageInference",
"taskUUID": "6cd4ba4a-9031-4690-bf30-c18e03147f01",
"model": "runware:97@1",
"positivePrompt": "A vast far-future monorail terminus beneath an immense stained-glass canopy, rain-slick platforms reflecting amber and cobalt light, suspended rail lines curving through the air, travelers in weatherproof capes carrying unusual luggage, hanging directional sigils, brass-and-ceramic ticket kiosks, giant ferns growing from engineered planters, flocks of mechanical swifts nesting in the rafters, distant skyline of layered habitation towers fading into mist, richly detailed architecture, dramatic depth, sharp focus, atmospheric perspective, intricate textures, cinematic composition, realistic lighting, highly detailed scene",
"width": 1024,
"height": 768,
"seed": 79278,
"steps": 30
}{
"taskType": "imageInference",
"taskUUID": "6cd4ba4a-9031-4690-bf30-c18e03147f01",
"imageUUID": "856fa7d3-972d-4078-be1b-981a8c9f4d46",
"imageURL": "https://im.runware.ai/image/os/a25d05/ws/2/ii/856fa7d3-972d-4078-be1b-981a8c9f4d46.jpg",
"seed": 79278,
"cost": 0.0083
}