StableDiffusionBridge provides on-device text-to-image generation. It is intended for apps that want local image generation without sending prompts or generated images to external servers.

Platform support#

Current support in the library code:

• Android: supported
• iOS: supported
• JVM / Desktop: supported
• WASM: currently not implemented

Public API#

expect object StableDiffusionBridge {
    fun getModelPath(modelFileName: String): String
    fun initModel(modelPath: String, threads: Int = -1): Boolean
    fun txt2img(
        prompt: String,
        negativePrompt: String? = null,
        width: Int = 512,
        height: Int = 512,
        steps: Int = 20,
        cfgScale: Float = 7.0f,
        seed: Long = -1L,
    ): ByteArray
    fun release()
}

getModelPath(modelFileName)#

Returns a usable path for the model file on the current platform.

val modelPath = StableDiffusionBridge.getModelPath("dreamshaper.safetensors")

initModel(modelPath, threads)#

Loads the Stable Diffusion model and creates the native context.

val ok = StableDiffusionBridge.initModel(modelPath, threads = 4)
check(ok) { "Failed to initialize Stable Diffusion model" }

Parameters#

• modelPath: absolute or platform-resolved path to the model file
• threads: CPU threads to use. Pass -1 to let the backend decide

You normally call this once and reuse the loaded model for multiple generations.

txt2img(...)#

Generates one image and returns the raw result as an RGBA byte array.

val rgba = StableDiffusionBridge.txt2img(
    prompt = "A cinematic photo of a llama astronaut",
    negativePrompt = "blurry, low quality, distorted",
    width = 512,
    height = 512,
    steps = 20,
    cfgScale = 7.5f,
    seed = 42L,
)

Parameters#

• prompt: what you want to generate
• negativePrompt: what you want the model to avoid
• width / height: output size in pixels
• steps: number of diffusion steps. Higher usually means slower but can improve quality
• cfgScale: how strongly the model should follow the prompt
• seed: controls reproducibility. Use a fixed value for repeatable output, or -1L for non-deterministic behavior

Return value#

The function returns an RGBA ByteArray of size width * height * 4. If generation fails, the returned array may be empty.

Converting the RGBA result#

The bridge returns raw pixels so you can decide how to display or save them on each platform.

Typical workflow:

• Android: convert the bytes into a Bitmap
• iOS: convert into UIImage / CoreGraphics image data
• Desktop: convert into BufferedImage

Pseudo-code idea:

val rgba = StableDiffusionBridge.txt2img(...)
check(rgba.isNotEmpty())
// Convert width/height/RGBA bytes into a platform image type

release()#

Frees the native Stable Diffusion context.

StableDiffusionBridge.release()

Call this when you are done with image generation or when the feature is being torn down.

Practical recommendations#

• Start with 512x512, steps = 20, cfgScale = 7.0f.
• Use a negative prompt for better consistency when quality matters.
• Reuse one initialized model for multiple generations instead of loading it every time.
• Expect significant CPU and memory use on mobile devices.