FLUX.2 [klein] 4B Base
FLUX.2 [klein] 4B Base is a compact undistilled image generation and editing model with an exceptional quality-to-size ratio. It is well suited for local deployment, efficient fine-tuning, and custom pipelines that require flexibility on limited hardware.
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.
-
outputType
string default: URL -
Image output type.
Allowed values 3 values
-
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
-
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
-
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.
-
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.
-
-
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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acceleration
string default: high -
Optimization level.
Allowed values 4 values
-
acceleratorOptions
object -
Advanced caching mechanisms to speed up generation.
Properties 12 properties
-
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.
-
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.
-
acceleratorOptions»cacheStartStepcacheStartStep
integer min: 0 -
Absolute step number to start caching. Must be less than
cacheEndStep.
-
acceleratorOptions»cacheStartStepPercentagecacheStartStepPercentage
integer min: 0 max: 99 -
Percentage of steps to start caching. Alternative to
cacheStartStep. Must be less thancacheEndStepPercentage.
-
acceleratorOptions»fbCachefbCache
boolean default: false -
First Block Cache (FBCache) acceleration. Reuses feature block computations across steps.
-
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.
-
acceleratorOptions»teaCacheteaCache
boolean default: false -
TeaCache acceleration for transformer-based models. Estimates step differences to skip redundant computations.
-
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.
-
acceleratorOptions»dbCachedbCache
boolean default: false -
DB Cache (CacheDiT) acceleration. Caches and reuses intermediate transformer block outputs to skip redundant computations.
-
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.
-
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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Inputs
Input resources for the task (images, audio, etc). These must be nested inside the inputs object.
inputs object.-
inputs»referenceImagesreferenceImages
array of strings min items: 1max items: 4 -
List of reference images (UUID, URL, Data URI, or Base64).
Generation Parameters
Core parameters for controlling the generated content.
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model
string required value: runware:400@5 -
Identifier of the model to use for generation.
Learn more 3 resources
-
positivePrompt
string required min: 1 max: 10000 -
Text prompt describing elements to include in the generated output.
Learn more 2 resources
-
negativePrompt
string min: 1 max: 10000 -
Prompt to guide what to exclude from generation. Ignored when guidance is disabled (CFGScale ≤ 1).
Learn more 1 resource
-
width
integer required min: 128 max: 2048 step: 16 -
Width of the generated media in pixels.
Learn more 2 resources
-
height
integer required min: 128 max: 2048 step: 16 -
Height of the generated media in pixels.
Learn more 2 resources
-
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
-
steps
integer min: 1 max: 50 default: 28 -
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
-
CFGScale
float min: 1 max: 20 step: 0.01 default: 3.5 -
Guidance scale representing how closely the output will resemble the prompt. Higher values produce results more aligned with the prompt.
Learn more 1 resource
-
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
-
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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Features
Standalone addons and post-processing features.
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advancedFeatures»ultralyticsultralytics
object -
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.
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.
Properties 8 properties
-
advancedFeatures»ultralytics»CFGScaleCFGScale
float min: 0 max: 50 step: 0.1 default: 8 -
Face refinement guidance scale.
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advancedFeatures»ultralytics»confidenceconfidence
float min: 0 max: 1 step: 0.01 default: 0.9 -
Confidence threshold for detection.
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advancedFeatures»ultralytics»maskBlurmaskBlur
integer min: 0 max: 100 default: 5 -
Mask feathering amount. Higher values create softer transitions between the enhanced face region and surrounding areas.
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advancedFeatures»ultralytics»maskPaddingmaskPadding
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.
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advancedFeatures»ultralytics»negativePromptnegativePrompt
string -
Negative prompt for detection.
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advancedFeatures»ultralytics»positivePromptpositivePrompt
string -
Positive prompt for detection.
-
advancedFeatures»ultralytics»stepssteps
integer min: 1 max: 100 default: 20 -
Number of face refinement steps.
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advancedFeatures»ultralytics»strengthstrength
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.
-
Tidal Archive Reading Hall
{
"taskType": "imageInference",
"taskUUID": "ac17b01d-8c5d-46f9-bd42-227280d05ff3",
"model": "runware:400@5",
"positivePrompt": "An immense tidal reading hall built inside a partially flooded stone basilica, concentric wooden walkways above clear seawater, archivists in practical rain capes sorting giant atlases, white ibises resting on railings, coral-encrusted columns, suspended rope shelves, brass instruments, damp parchment, drifting motes, luminous shafts of daylight through high arches, elegant environmental storytelling, intricate textures, cinematic scale, natural color palette, crisp details, imaginative yet believable architecture",
"negativePrompt": "text, watermark, logo, frame, blurry, low detail, oversaturated, distorted anatomy, duplicated objects, chaotic composition, flat lighting",
"width": 1152,
"height": 768,
"seed": 98694,
"steps": 32,
"CFGScale": 3.5,
"settings": {
"trueCFGScale": 4
},
"inputs": {
"referenceImages": [
"https://assets.runware.ai/assets/inputs/cfa98149-a68b-4386-b745-6c8c1c1fac4a.jpg",
"https://assets.runware.ai/assets/inputs/51b9893d-5473-4c97-83b7-cc5f87b3c746.jpg",
"https://assets.runware.ai/assets/inputs/c368b834-ca8e-45ea-88d0-69372304531a.jpg"
]
}
}{
"taskType": "imageInference",
"taskUUID": "ac17b01d-8c5d-46f9-bd42-227280d05ff3",
"imageUUID": "dcccec94-b421-4dae-bb19-45511def2245",
"imageURL": "https://im.runware.ai/image/os/a14d18/ws/2/ii/dcccec94-b421-4dae-bb19-45511def2245.jpg",
"seed": 98694,
"cost": 0.0109
}Patchwork Carnival Aerostat Regatta
{
"taskType": "imageInference",
"taskUUID": "234735c5-3f14-41f5-b1a1-eac2d1e15226",
"model": "runware:400@5",
"positivePrompt": "A jubilant regatta of patchwork aerostats drifting above a terraced festival town, huge handmade balloon craft stitched from patterned cloth, dangling bells and ribbons, inventive copper propellers, whimsical gondolas filled with musicians and acrobats, swirling confetti, layered rooftops, carved wooden balconies, sun-washed clouds, dynamic diagonal composition, highly detailed textures, painterly yet believable, imaginative worldbuilding, vibrant but tasteful color harmony, cinematic scale",
"negativePrompt": "text, watermark, logo, blurry, low detail, extra limbs, distorted anatomy, duplicate balloons, flat lighting, oversaturated, empty background, modern cars, skyscrapers",
"width": 1280,
"height": 720,
"seed": 52976,
"steps": 28,
"CFGScale": 3.5,
"settings": {
"trueCFGScale": 4
},
"inputs": {
"referenceImages": [
"https://assets.runware.ai/assets/inputs/a3e29ef6-993a-43ab-8c40-76394eea8ae8.jpg",
"https://assets.runware.ai/assets/inputs/38088571-7b0b-477b-953d-76afb59a1105.jpg",
"https://assets.runware.ai/assets/inputs/b6277191-fdb5-42aa-8ee0-8afa4ca75dd4.jpg"
]
}
}{
"taskType": "imageInference",
"taskUUID": "234735c5-3f14-41f5-b1a1-eac2d1e15226",
"imageUUID": "59fb7b42-aba6-436a-875b-e096e816cdfe",
"imageURL": "https://im.runware.ai/image/os/a20d05/ws/2/ii/59fb7b42-aba6-436a-875b-e096e816cdfe.jpg",
"seed": 52976,
"cost": 0.009
}Windmill Library Among Reedbeds
{
"taskType": "imageInference",
"taskUUID": "4d3a4156-5e5e-45db-b73c-a3200a7446ed",
"model": "runware:400@5",
"positivePrompt": "An old timber windmill converted into a public library, rising from a wide marsh of golden reedbeds and shallow reflective water, linked by narrow wooden footbridges and tiny reading docks. Stacks of books visible through circular windows, weathered sails patched with canvas, hand-painted signs, bicycles leaning near the entrance, migratory birds wheeling overhead, scattered lanterns glowing softly in early morning mist, a small rowboat filled with returned books, layered clouds opening to pale sunlight. Highly detailed natural textures, cinematic composition, storybook realism, delicate color harmony, crisp focus, atmospheric depth, charming human-scale details, painterly yet believable scene.",
"negativePrompt": "low detail, blurry, distorted architecture, duplicate objects, extra limbs, people close-up, oversaturated, flat lighting, text watermark, logo, frame, harsh CGI, noisy image",
"width": 1024,
"height": 768,
"seed": 32975,
"steps": 28,
"CFGScale": 3.5,
"settings": {
"trueCFGScale": 4
}
}{
"taskType": "imageInference",
"taskUUID": "4d3a4156-5e5e-45db-b73c-a3200a7446ed",
"imageUUID": "60c92bc8-5e1e-44fb-bb14-3df4489a0a71",
"imageURL": "https://im.runware.ai/image/os/a04d20/ws/2/ii/60c92bc8-5e1e-44fb-bb14-3df4489a0a71.jpg",
"seed": 32975,
"cost": 0.0019
}Subterranean Fungal Transit Platform
{
"taskType": "imageInference",
"taskUUID": "93b230ca-1b1d-4a48-81a4-4e91632aafdb",
"model": "runware:400@5",
"positivePrompt": "A vast underground train platform carved into ancient stone caverns, giant shelf mushrooms and tangled pale fungi growing from columns and archways, a copper-and-wood commuter rail waiting beside the platform, passengers in weathered rain capes carrying wicker baskets and mechanical lanterns, overhead mineral chandeliers made from quartz and brass, puddles reflecting warm amber station lamps, hand-painted wayfinding signs in a forgotten script, drifting steam, detailed masonry, cinematic depth, atmospheric haze, intricate textures, grounded fantasy realism, wide environmental composition, highly detailed",
"negativePrompt": "low detail, blurry, distorted anatomy, extra limbs, duplicated people, modern city setting, cars, skyscrapers, text watermark, logo, oversaturated colors, flat lighting, empty scene",
"width": 1024,
"height": 640,
"seed": 78524,
"steps": 28,
"CFGScale": 3.5,
"settings": {
"trueCFGScale": 4
}
}{
"taskType": "imageInference",
"taskUUID": "93b230ca-1b1d-4a48-81a4-4e91632aafdb",
"imageUUID": "437c2f04-1b91-4fed-aa7d-99abb4b7c0ad",
"imageURL": "https://im.runware.ai/image/os/a15d18/ws/2/ii/437c2f04-1b91-4fed-aa7d-99abb4b7c0ad.jpg",
"seed": 78524,
"cost": 0.0013
}