diff --git a/packages/react-native-executorch/src/extensions/cv/ops/boxes.ts b/packages/react-native-executorch/src/extensions/cv/ops/boxes.ts
index 8360472980..a5b12287a3 100644
--- a/packages/react-native-executorch/src/extensions/cv/ops/boxes.ts
+++ b/packages/react-native-executorch/src/extensions/cv/ops/boxes.ts
@@ -8,9 +8,24 @@ import { scalePoint } from './points';
  * @category Types
  */
 export type BoxMap = {
-  xyxy: { xmin: number; ymin: number; xmax: number; ymax: number };
-  xywh: { xmin: number; ymin: number; w: number; h: number };
-  cxcywh: { cx: number; cy: number; w: number; h: number };
+  xyxy: {
+    readonly xmin: number;
+    readonly ymin: number;
+    readonly xmax: number;
+    readonly ymax: number;
+  };
+  xywh: {
+    readonly xmin: number;
+    readonly ymin: number;
+    readonly w: number;
+    readonly h: number;
+  };
+  cxcywh: {
+    readonly cx: number;
+    readonly cy: number;
+    readonly w: number;
+    readonly h: number;
+  };
 };
 
 /**
@@ -130,9 +145,16 @@ export function scaleBox<F extends BoxFormat>(
  * @category Types
  */
 export type NmsOptions = {
+  /** Bounding box format (`xyxy`, `cxcywh`, etc.). */
   readonly boxFormat: BoxFormat;
+  /** IoU threshold for suppressing overlapping boxes. */
   readonly iouThreshold: number;
+  /** Minimum confidence score threshold for filtering candidate boxes. */
   readonly confidenceThreshold: number;
+  /**
+   * NMS algorithm variant (`standard` for hard suppression, `weighted` for soft
+   * coordinate averaging).
+   */
   readonly nmsType: 'standard' | 'weighted';
 };
 
@@ -142,7 +164,13 @@ export type NmsOptions = {
  * @category Utils
  * @param boxes Bounding boxes coordinate tensor.
  * @param scores Bounding boxes confidence scores tensor.
- * @param opts Options configure NMS thresholds and execution mode.
+ * @param opts Options configuring NMS thresholds and execution mode.
+ * @param opts.boxFormat Bounding box format (`xyxy`, `cxcywh`, etc.).
+ * @param opts.iouThreshold Intersection over Union (IoU) threshold for
+ * suppression.
+ * @param opts.confidenceThreshold Minimum confidence score for candidate
+ * selection.
+ * @param opts.nmsType Suppression algorithm mode (`standard` or `weighted`).
  * @returns The resulting indices of the non-suppressed boxes:
  * - For `standard` NMS: A 1D array of indices (`number[]`) representing the
  *   selected boxes.
diff --git a/packages/react-native-executorch/src/extensions/cv/ops/image.ts b/packages/react-native-executorch/src/extensions/cv/ops/image.ts
index 1d98b73c41..b484332dad 100644
--- a/packages/react-native-executorch/src/extensions/cv/ops/image.ts
+++ b/packages/react-native-executorch/src/extensions/cv/ops/image.ts
@@ -74,8 +74,11 @@ export type InterpolationMethod = 'nearest' | 'area' | 'cubic' | 'lanczos' | 'li
  * @category Types
  */
 export type ResizeOptions = {
+  /** Resize algorithm mode (`stretch`, `letterbox`, `crop`). */
   readonly mode?: ResizeMode;
+  /** Background fill value used when letterboxing. */
   readonly padValue?: number;
+  /** Pixel interpolation method. */
   readonly interpolation?: InterpolationMethod;
 };
 
@@ -84,7 +87,9 @@ export type ResizeOptions = {
  * @category Types
  */
 export type NormalizeOptions = {
+  /** Multiplicative scaling coefficient(s). */
   readonly alpha?: number | readonly number[];
+  /** Additive offset coefficient(s). */
   readonly beta?: number | readonly number[];
 };
 
@@ -99,6 +104,11 @@ export type NormalizeOptions = {
  * to. `dst` must be in HWC layout and its number of channels must match `src`.
  * Shape [H',W',C].
  * @param opts Configuration options for resizing.
+ * @param opts.mode Resize algorithm mode (`stretch`, `letterbox`, `crop`).
+ * Defaults to `'stretch'`.
+ * @param opts.interpolation Pixel interpolation method (`linear`, `lanczos`,
+ * etc.). Defaults to `'lanczos'`.
+ * @param opts.padValue Fill value for letterboxing. Defaults to `0`.
  * @returns The destination tensor containing the resized image.
  */
 export function resize(src: Tensor, dst: Tensor, opts?: ResizeOptions): Tensor {
@@ -173,6 +183,9 @@ export function toChannelsLast(src: Tensor, dst: Tensor): Tensor {
  * @param dst The pre-allocated destination tensor to write the normalized
  * values to. `dst` must have the same shape as `src`. Shape [C,H,W].
  * @param opts Normalization scaling coefficients.
+ * @param opts.alpha Multiplicative scaling coefficient(s). Defaults to
+ * `1 / 255.0`.
+ * @param opts.beta Additive offset coefficient(s). Defaults to `0.0`.
  * @returns The destination tensor containing the normalized image.
  */
 export function normalize(src: Tensor, dst: Tensor, opts?: NormalizeOptions): Tensor {
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/classification.ts b/packages/react-native-executorch/src/extensions/cv/tasks/classification.ts
index 3a8b2d244c..a621888d66 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/classification.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/classification.ts
@@ -14,15 +14,20 @@ import { createImagePreprocessor, type ImagePreprocessorOptions } from './prepro
  * vocabulary.
  * @category Types
  */
-export type ClassifierOptions<L> = ImagePreprocessorOptions & { readonly labels: readonly L[] };
+export type ClassifierOptions<L> = ImagePreprocessorOptions & {
+  /** Array of class labels matching the model's output vocabulary. */
+  readonly labels: readonly L[];
+};
 
 /**
  * Model configuration required to instantiate a classifier task runner.
  * @category Types
  */
 export type ClassifierModel<L> = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
-  readonly classifierOpts: ClassifierOptions<L>;
+  /** Image preprocessor and vocabulary options. */
+  readonly opts: ClassifierOptions<L>;
 };
 
 /**
@@ -30,7 +35,9 @@ export type ClassifierModel<L> = {
  * @category Types
  */
 export type Classification<L> = {
+  /** Predicted class label. */
   readonly label: L;
+  /** Confidence score of the prediction (between 0.0 and 1.0). */
   readonly confidence: number;
 };
 
@@ -74,7 +81,7 @@ export async function createClassifier<L>(
    */
   classifyWorklet: (input: ImageBuffer, options?: { topk?: number }) => Classification<L>[];
 }> {
-  const { modelPath, classifierOpts } = config;
+  const { modelPath, opts } = config;
   const model = await wrapAsync(loadModel, runtime)(modelPath);
 
   const meta = validateModelSchema(
@@ -87,9 +94,9 @@ export async function createClassifier<L>(
   const outShape = meta.outputTensorMeta[0]!.shape;
 
   const numLabels = outShape[outShape.length - 1]!;
-  if (classifierOpts.labels.length !== numLabels) {
+  if (opts.labels.length !== numLabels) {
     throw new Error(
-      `Classifier labels length (${classifierOpts.labels.length}) must match model output dimension (${numLabels}).`
+      `Classifier labels length (${opts.labels.length}) must match model output dimension (${numLabels}).`
     );
   }
 
@@ -100,7 +107,7 @@ export async function createClassifier<L>(
   ] as const;
 
   const [tLogits, tProbas] = tensors;
-  const preprocessor = createImagePreprocessor(classifierOpts, inpShape);
+  const preprocessor = createImagePreprocessor(opts, inpShape);
 
   const dispose = () => {
     preprocessor.dispose();
@@ -125,7 +132,7 @@ export async function createClassifier<L>(
       .getData(new Float32Array(tProbas.numel));
 
     return Array.from(probas)
-      .map((confidence, index) => ({ confidence, label: classifierOpts.labels[index]! }))
+      .map((confidence, index) => ({ confidence, label: opts.labels[index]! }))
       .sort((a, b) => b.confidence - a.confidence)
       .slice(0, options?.topk);
   };
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/imageEmbedding.ts b/packages/react-native-executorch/src/extensions/cv/tasks/imageEmbedding.ts
index afd4c63383..0aaca44933 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/imageEmbedding.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/imageEmbedding.ts
@@ -13,7 +13,9 @@ import { createImagePreprocessor, type ImagePreprocessorOptions } from './prepro
  * @category Types
  */
 export type ImageEmbedderModel = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
+  /** Image preprocessor options. */
   readonly opts: ImagePreprocessorOptions;
 };
 
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/instanceSegmentation.ts b/packages/react-native-executorch/src/extensions/cv/tasks/instanceSegmentation.ts
index d26407ea39..9440a8f081 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/instanceSegmentation.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/instanceSegmentation.ts
@@ -31,11 +31,17 @@ export type InstanceSegmenterOptions<F extends BoxFormat, L> = Omit<
   ImagePreprocessorOptions,
   'resizeMode'
 > & {
+  /** Resize mode for input images. */
   readonly resizeMode: 'stretch';
+  /** Array of class labels matching the model's output vocabulary. */
   readonly labels: readonly L[];
+  /** Bounding box format exported by the model (`xyxy`, `cxcywh`, etc.). */
   readonly boxFormat: F;
+  /** Default IoU threshold for Non-Maximum Suppression (NMS). */
   readonly defaultIouThreshold: number;
+  /** Default probability threshold for mask values. */
   readonly defaultMaskThreshold: number;
+  /** Default minimum confidence score threshold for detected instances. */
   readonly defaultConfidenceThreshold: number;
 };
 
@@ -46,7 +52,9 @@ export type InstanceSegmenterOptions<F extends BoxFormat, L> = Omit<
  * @typeParam L The label type.
  */
 export type InstanceSegmenterModel<F extends BoxFormat, L> = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
+  /** Instance segmenter options. */
   readonly opts: InstanceSegmenterOptions<F, L>;
 };
 
@@ -58,9 +66,13 @@ export type InstanceSegmenterModel<F extends BoxFormat, L> = {
  * @typeParam L The label type.
  */
 export type InstanceSegmentationResult<F extends BoxFormat, L> = {
+  /** Scaled bounding box coordinates matching the input image resolution. */
   readonly box: BoundingBox<F>;
+  /** Binary segmentation mask buffer cropped to the instance bounding box. */
   readonly mask: ImageBuffer;
+  /** Predicted instance class label. */
   readonly label: L;
+  /** Confidence score of the instance detection (between 0.0 and 1.0). */
   readonly confidence: number;
 };
 
@@ -93,10 +105,12 @@ export async function createInstanceSegmenter<F extends BoxFormat, L>(
    * Performs asynchronous instance segmentation on the given input image.
    * @param input The input image buffer.
    * @param options Execution override options.
-   * @param options.confidenceThreshold Override for the minimum confidence
-   * threshold.
-   * @param options.iouThreshold Override for the IoU threshold in NMS.
-   * @param options.maskThreshold Override for the mask binarization threshold.
+   * @param options.confidenceThreshold Minimum confidence threshold. If
+   * omitted, uses `opts.defaultConfidenceThreshold`.
+   * @param options.iouThreshold IoU threshold in NMS. If omitted, uses
+   * `opts.defaultIouThreshold`.
+   * @param options.maskThreshold Mask binarization threshold. If omitted,
+   * uses `opts.defaultMaskThreshold`.
    * @returns A promise resolving to a list of detected instances.
    */
   segmentInstances: (
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/keypointDetection.ts b/packages/react-native-executorch/src/extensions/cv/tasks/keypointDetection.ts
index d6ea03a294..242cffccbb 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/keypointDetection.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/keypointDetection.ts
@@ -22,10 +22,15 @@ export type KeypointDetectorOptions<F extends BoxFormat, L extends PropertyKey>
   ImagePreprocessorOptions,
   'resizeMode'
 > & {
+  /** Resize mode for preprocessing input images (`stretch` or `letterbox`). */
   readonly resizeMode: Exclude<ResizeMode, 'crop'>;
+  /** Bounding box format exported by the model (`xyxy`, `cxcywh`, etc.). */
   readonly boxFormat: F;
+  /** Array of landmark names matching the model output keypoint locations. */
   readonly landmarks: readonly L[];
+  /** Default IoU threshold for Non-Maximum Suppression (NMS). */
   readonly defaultIouThreshold: number;
+  /** Default minimum confidence score threshold for keypoint detections. */
   readonly defaultConfidenceThreshold: number;
 };
 
@@ -34,7 +39,9 @@ export type KeypointDetectorOptions<F extends BoxFormat, L extends PropertyKey>
  * @category Types
  */
 export type KeypointDetectorModel<F extends BoxFormat, L extends PropertyKey> = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
+  /** Keypoint detector options. */
   readonly opts: KeypointDetectorOptions<F, L>;
 };
 
@@ -51,8 +58,11 @@ export type Landmarks<L extends PropertyKey> = Record<L, Point & { readonly conf
  * @category Types
  */
 export type KeypointDetection<F extends BoxFormat, L extends PropertyKey> = {
+  /** Scaled bounding box coordinates matching the input image resolution. */
   readonly box: BoundingBox<F>;
+  /** Overall confidence score of the detection (between 0.0 and 1.0). */
   readonly confidence: number;
+  /** Map of landmark names to their scaled pixel coordinates and individual confidence scores. */
   readonly landmarks: Landmarks<L>;
 };
 
@@ -160,9 +170,9 @@ export async function createKeypointDetector<F extends BoxFormat, L extends Prop
    * @param input The input image buffer.
    * @param options Configuration options for keypoint detection.
    * @param options.confidenceThreshold Minimum confidence score for a
-   * detection. If omitted, uses the model default.
+   * detection. If omitted, uses `opts.defaultConfidenceThreshold`.
    * @param options.iouThreshold Intersection over Union (IoU) threshold for
-   * NMS. If omitted, uses the model default.
+   * NMS. If omitted, uses `opts.defaultIouThreshold`.
    * @returns A promise resolving to the list of keypoint detections.
    */
   detectKeypoints: (
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/objectDetection.ts b/packages/react-native-executorch/src/extensions/cv/tasks/objectDetection.ts
index f3289dfc5b..efa9d410ca 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/objectDetection.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/objectDetection.ts
@@ -21,10 +21,15 @@ export type ObjectDetectorOptions<F extends BoxFormat, L> = Omit<
   ImagePreprocessorOptions,
   'resizeMode'
 > & {
+  /** Resize mode for preprocessing input images (`stretch` or `letterbox`). */
   readonly resizeMode: Exclude<ResizeMode, 'crop'>;
+  /** Array of class labels matching the model's output vocabulary. */
   readonly labels: readonly L[];
+  /** Bounding box format exported by the model (`xyxy`, `cxcywh`, etc.). */
   readonly boxFormat: F;
+  /** Default IoU threshold for Non-Maximum Suppression (NMS). */
   readonly defaultIouThreshold: number;
+  /** Default minimum confidence score threshold for detections. */
   readonly defaultConfidenceThreshold: number;
 };
 
@@ -33,7 +38,9 @@ export type ObjectDetectorOptions<F extends BoxFormat, L> = Omit<
  * @category Types
  */
 export type ObjectDetectorModel<F extends BoxFormat, L> = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
+  /** Object detector preprocessor and threshold options. */
   readonly opts: ObjectDetectorOptions<F, L>;
 };
 
@@ -42,8 +49,11 @@ export type ObjectDetectorModel<F extends BoxFormat, L> = {
  * @category Types
  */
 export type ObjectDetection<F extends BoxFormat, L> = {
+  /** Scaled bounding box coordinates matching the input image resolution. */
   readonly box: BoundingBox<F>;
+  /** Predicted object class label. */
   readonly label: L;
+  /** Confidence score of the detection (between 0.0 and 1.0). */
   readonly confidence: number;
 };
 
@@ -72,12 +82,12 @@ export async function createObjectDetector<F extends BoxFormat, L>(
    */
   dispose: () => void;
   /**
-   * Performs asynchronous object detection on the given input image.
    * @param input The input image buffer.
    * @param options Configuration options for object detection.
-   * @param options.confidenceThreshold Minimum confidence score for returned
-   * detections.
-   * @param options.iouThreshold Non-maximum suppression IoU threshold.
+   * @param options.confidenceThreshold Minimum confidence score threshold. If
+   * omitted, uses `opts.defaultConfidenceThreshold`.
+   * @param options.iouThreshold Non-maximum suppression IoU threshold. If
+   * omitted, uses `opts.defaultIouThreshold`.
    * @returns A promise resolving to the list of object detections.
    */
   detectObjects: (
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/preprocessing.ts b/packages/react-native-executorch/src/extensions/cv/tasks/preprocessing.ts
index 3569210481..df9f438d72 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/preprocessing.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/preprocessing.ts
@@ -5,6 +5,7 @@ import type { ImageBuffer } from '../image';
 import {
   type ResizeMode,
   type InterpolationMethod,
+  type NormalizeOptions,
   FORMAT_CONVERSION,
   FORMAT_CHANNELS,
   resize,
@@ -18,10 +19,13 @@ import {
  * @category Types
  */
 export type ImagePreprocessorOptions = {
+  /** Resize algorithm mode (`stretch`, `letterbox`, `crop`). */
   readonly resizeMode: ResizeMode;
+  /** Pixel interpolation method (`linear`, `lanczos`, etc.). */
   readonly interpolation: InterpolationMethod;
-  readonly alpha: number | readonly number[];
-  readonly beta: number | readonly number[];
+  /** Normalization scaling coefficients. */
+  readonly normalizeOpts: NormalizeOptions;
+  /** Optional background fill value used when letterboxing. */
   readonly padValue?: number;
 };
 
@@ -84,7 +88,7 @@ export function createImagePreprocessor(
   ] as const;
 
   const [tColor, tChanFirst, tNorm, tOutput] = tensors;
-  const { resizeMode, interpolation, alpha, beta, padValue } = opts;
+  const { resizeMode, interpolation, normalizeOpts, padValue } = opts;
 
   const dispose = () => tensors.forEach((t) => t.dispose());
   const process = (input: ImageBuffer): Tensor => {
@@ -105,7 +109,7 @@ export function createImagePreprocessor(
         })
         .throughIf(colorCode !== null, cvtColor, tColor, colorCode!)
         .through(toChannelsFirst, tChanFirst)
-        .through(normalize, tNorm, { alpha, beta })
+        .through(normalize, tNorm, normalizeOpts)
         .copyTo(tOutput);
     } finally {
       tInput.dispose();
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/semanticSegmentation.ts b/packages/react-native-executorch/src/extensions/cv/tasks/semanticSegmentation.ts
index 148cf9b267..fd08d34bbf 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/semanticSegmentation.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/semanticSegmentation.ts
@@ -22,9 +22,12 @@ import { sigmoid, argmax } from '../../math';
  * vocabulary.
  * @category Types
  */
-export type SemanticSegmentationOptions<L> = Omit<ImagePreprocessorOptions, 'resizeMode'> & {
+export type SemanticSegmenterOptions<L> = Omit<ImagePreprocessorOptions, 'resizeMode'> & {
+  /** Resize mode for input images. */
   readonly resizeMode: 'stretch';
+  /** Interpolation method used when resizing output masks back to input image dimensions. */
   readonly outInterpolation: InterpolationMethod;
+  /** Array of class labels matching the model's output vocabulary. */
   readonly labels: readonly L[];
 };
 
@@ -32,9 +35,11 @@ export type SemanticSegmentationOptions<L> = Omit<ImagePreprocessorOptions, 'res
  * Model configuration required to instantiate a segmenter task runner.
  * @category Types
  */
-export type SemanticSegmentationModel<L> = {
+export type SemanticSegmenterModel<L> = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
-  readonly opts: SemanticSegmentationOptions<L>;
+  /** Semantic segmenter options. */
+  readonly opts: SemanticSegmenterOptions<L>;
 };
 
 /**
@@ -48,8 +53,10 @@ export type ColorMap<L extends PropertyKey> = Record<L, [number, number, number,
  * @category Types
  */
 export type SemanticSegmentationResult<L extends PropertyKey> = {
-  buffer: ImageBuffer;
-  colormap?: ColorMap<L>;
+  /** Generated output RGBA image buffer containing the colored segmentation mask. */
+  readonly buffer: ImageBuffer;
+  /** Applied color map mapping each class label to its RGBA tuple. */
+  readonly colormap?: ColorMap<L>;
 };
 
 function hslToRgb(h: number, s: number, l: number): [number, number, number] {
@@ -77,7 +84,7 @@ function hslToRgb(h: number, s: number, l: number): [number, number, number] {
  * disposal controls.
  */
 export async function createSemanticSegmenter<L extends PropertyKey = string>(
-  config: SemanticSegmentationModel<L>,
+  config: SemanticSegmenterModel<L>,
   runtime?: WorkletRuntime
 ): Promise<{
   /**
diff --git a/packages/react-native-executorch/src/extensions/cv/tasks/styleTransfer.ts b/packages/react-native-executorch/src/extensions/cv/tasks/styleTransfer.ts
index 1c1a89cbe5..7e2d97caca 100644
--- a/packages/react-native-executorch/src/extensions/cv/tasks/styleTransfer.ts
+++ b/packages/react-native-executorch/src/extensions/cv/tasks/styleTransfer.ts
@@ -13,6 +13,7 @@ import {
   cvtColor,
   resize,
   type InterpolationMethod,
+  type NormalizeOptions,
 } from '../ops/image';
 
 /**
@@ -20,9 +21,11 @@ import {
  * @category Types
  */
 export type StyleTransferOptions = Omit<ImagePreprocessorOptions, 'resizeMode'> & {
+  /** Resize mode for input images. */
   readonly resizeMode: 'stretch';
-  readonly outAlpha: number | number[];
-  readonly outBeta: number | number[];
+  /** Normalization options for postprocessing output tensors back to uint8 pixel values. */
+  readonly outNormalizeOpts: NormalizeOptions;
+  /** Interpolation method used when resizing output styled images to input dimensions. */
   readonly outInterpolation: InterpolationMethod;
 };
 
@@ -31,7 +34,9 @@ export type StyleTransferOptions = Omit<ImagePreprocessorOptions, 'resizeMode'>
  * @category Types
  */
 export type StyleTransferModel = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
+  /** Style transfer preprocessor and postprocessor options. */
   readonly opts: StyleTransferOptions;
 };
 
@@ -108,7 +113,7 @@ export async function createStyleTransfer(
     try {
       tOutput
         .copyTo(tReshape)
-        .through(normalize, tUint8, { alpha: opts.outAlpha, beta: opts.outBeta })
+        .through(normalize, tUint8, opts.outNormalizeOpts)
         .through(toChannelsLast, tChanLast)
         .through(cvtColor, tRgba, 'RGB2RGBA')
         .through(resize, tResize, { mode: 'stretch', interpolation: opts.outInterpolation })
diff --git a/packages/react-native-executorch/src/extensions/nlp/tasks/textEmbedding.ts b/packages/react-native-executorch/src/extensions/nlp/tasks/textEmbedding.ts
index 857457d89f..9b5859b540 100644
--- a/packages/react-native-executorch/src/extensions/nlp/tasks/textEmbedding.ts
+++ b/packages/react-native-executorch/src/extensions/nlp/tasks/textEmbedding.ts
@@ -12,8 +12,11 @@ import { loadTokenizer } from '../tokenizer';
  * @category Types
  */
 export type TextEmbedderModel = {
+  /** Local path or remote URL of the `.pte` model file. */
   readonly modelPath: string;
+  /** Local path or remote URL of the tokenizer file. */
   readonly tokenizerPath: string;
+  /** Optional default prompt prefix added to input text before embedding. */
   readonly defaultPrompt?: string;
 };
 
diff --git a/packages/react-native-executorch/src/extensions/speech/tasks/fsmnVoiceActivityDetection.ts b/packages/react-native-executorch/src/extensions/speech/tasks/fsmnVoiceActivityDetection.ts
index 9225c743ff..8e1dc354c2 100644
--- a/packages/react-native-executorch/src/extensions/speech/tasks/fsmnVoiceActivityDetection.ts
+++ b/packages/react-native-executorch/src/extensions/speech/tasks/fsmnVoiceActivityDetection.ts
@@ -33,35 +33,35 @@ const DEFAULT_DETECTION_MARGIN_MS = 100;
  * Tunable thresholds controlling how per-frame speech probabilities are turned
  * into speech {@link Segment}s.
  * @category Types
- * @property {number} [speechThreshold] - Minimum speech probability (0-1) for a
- * frame to count as speech. Defaults to `0.6`.
- * @property {number} [minSpeechDurationMs] - Minimum duration a region must stay
- * above the threshold to open a segment. Defaults to `250`.
- * @property {number} [minSilenceDurationMs] - Minimum duration below the
- * threshold required to close a segment. Defaults to `100`.
- * @property {number} [speechPadMs] - Padding added to both ends of every
- * detected segment. Defaults to `30`.
- * @property {number} [mergeGapMs] - Segments closer than this gap are merged
- * into one. Defaults to `0`.
  */
 export type VadOptions = {
+  /** Minimum speech probability (0-1) for a frame to count as speech. */
   readonly speechThreshold?: number;
+  /**
+   * Minimum duration a region must stay above the threshold to open a
+   * segment.
+   */
   readonly minSpeechDurationMs?: number;
+  /** Minimum duration below threshold required to close a segment. */
   readonly minSilenceDurationMs?: number;
+  /** Padding added to both ends of every detected segment. */
   readonly speechPadMs?: number;
+  /** Segments closer than this gap are merged into one. */
   readonly mergeGapMs?: number;
 };
 
 /**
  * Model configuration required to instantiate an FSMN-VAD task runner.
  * @category Types
- * @property {string} modelPath - Local path or remote URL of the `.pte` model.
- * @property {Required<VadOptions>} defaultOptions - Detection thresholds tuned
- * for this model, overridable per `detectVoice` call. Defined alongside the
- * model in the `models` registry so the defaults are discoverable there.
  */
 export type FsmnVadModel = {
+  /** Local path or remote URL of the `.pte` model. */
   readonly modelPath: string;
+  /**
+   * Detection thresholds tuned for this model, overridable per `detectVoice`
+   * call. Defined alongside the model in the `models` registry so defaults
+   * are discoverable there.
+   */
   readonly defaultOptions: Required<VadOptions>;
 };
 
@@ -70,7 +70,9 @@ export type FsmnVadModel = {
  * @category Types
  */
 export type Segment = {
+  /** Start time of the speech segment in seconds. */
   readonly start: number;
+  /** End time of the speech segment in seconds. */
   readonly end: number;
 };
 
@@ -78,11 +80,12 @@ export type Segment = {
  * Options controlling live detection via `detectVoiceOnStream`. Extends the
  * per-call detection thresholds ({@link VadOptions}).
  * @category Types
- * @property {number} [detectionMargin] - How recent (in milliseconds) the last
- * detected speech segment must reach toward the end of the window for speech to
- * still be considered ongoing. Defaults to `100`.
  */
 export type VadStreamOptions = VadOptions & {
+  /**
+   * How recent (in milliseconds) the last detected speech segment must reach
+   * toward the end of the window for speech to still be considered ongoing.
+   */
   readonly detectionMargin?: number;
 };
 
diff --git a/packages/react-native-executorch/src/extensions/speech/tasks/whisperSpeechToText.ts b/packages/react-native-executorch/src/extensions/speech/tasks/whisperSpeechToText.ts
index dcd71f9bc4..f5d0db9bbe 100644
--- a/packages/react-native-executorch/src/extensions/speech/tasks/whisperSpeechToText.ts
+++ b/packages/react-native-executorch/src/extensions/speech/tasks/whisperSpeechToText.ts
@@ -55,11 +55,13 @@ export type WhisperLanguage = (typeof WHISPER_LANGUAGES)[number];
 /**
  * Options passed to a single transcription call.
  * @category Types
- * @property language - Whisper language code of the spoken audio. Must be one of
- * the {@link WhisperLanguage} values declared in the model's
- * `supportedLanguages` list.
  */
 export type WhisperSttOptions<L extends WhisperLanguage = WhisperLanguage> = {
+  /**
+   * Whisper language code of the spoken audio. Must be one of
+   * the {@link WhisperLanguage} values declared in the model's
+   * `supportedLanguages` list.
+   */
   readonly language: L;
 };
 
@@ -67,20 +69,28 @@ export type WhisperSttOptions<L extends WhisperLanguage = WhisperLanguage> = {
  * Options for the live-streaming transcription API.
  * Extends {@link WhisperSttOptions} with optional VAD tuning.
  * @category Types
- * @property vadOptions - Fine-tuning knobs forwarded to the voice-activity
- * detector. Omit to use the detector's built-in defaults.
  */
 export type WhisperStreamOptions<L extends WhisperLanguage = WhisperLanguage> =
-  WhisperSttOptions<L> & { readonly vadOptions?: VadStreamOptions };
+  WhisperSttOptions<L> & {
+    /**
+     * Fine-tuning knobs forwarded to the voice-activity detector. Omit to use
+     * built-in defaults.
+     */
+    readonly vadOptions?: VadStreamOptions;
+  };
 
 /**
  * Paths and metadata required to instantiate a Whisper speech-to-text model.
  * @category Types
  */
 export type WhisperSttModel<L extends WhisperLanguage = WhisperLanguage> = {
+  /** Local path or remote URL of the `.pte` model. */
   readonly modelPath: string;
+  /** Local path or remote URL of the tokenizer file. */
   readonly tokenizerPath: string;
+  /** List of supported language codes for this model. */
   readonly supportedLanguages: readonly L[];
+  /** VAD model configuration used for speech segmentation. */
   readonly vadModel: FsmnVadModel;
 };
 
diff --git a/packages/react-native-executorch/src/extensions/speech/utils/vadUtils.ts b/packages/react-native-executorch/src/extensions/speech/utils/vadUtils.ts
index 7b39705d64..12755c281e 100644
--- a/packages/react-native-executorch/src/extensions/speech/utils/vadUtils.ts
+++ b/packages/react-native-executorch/src/extensions/speech/utils/vadUtils.ts
@@ -4,13 +4,13 @@ import { type Tensor } from '../../../core/tensor';
 /**
  * Options controlling how {@link extractFrames} slices and filters the waveform.
  * @category Types
- * @property {number} numFrames - Number of frames to write (must be `<= dst.shape[0]`).
- * @property {number} hopLength - Samples between consecutive frames.
- * @property {number} preemphasis - Pre-emphasis filter coefficient.
  */
 export type ExtractFramesOptions = {
+  /** Number of audio frames to extract and write into the destination tensor. */
   readonly numFrames: number;
+  /** Samples between consecutive frames. */
   readonly hopLength: number;
+  /** Pre-emphasis filter coefficient. */
   readonly preemphasis: number;
 };
 
@@ -27,6 +27,10 @@ export type ExtractFramesOptions = {
  * @param hann Precomputed Hann window, shape `[frameLength]`.
  * @param dst Pre-allocated destination, shape `[frames, fftLength]`.
  * @param options Framing options.
+ * @param options.numFrames Number of frames to write (must not exceed `dst`
+ * tensor's first dimension `dst.shape[0]`).
+ * @param options.hopLength Number of audio samples between consecutive frames.
+ * @param options.preemphasis Pre-emphasis filter coefficient.
  * @returns The `dst` tensor, for convenience.
  */
 export function extractFrames(
diff --git a/packages/react-native-executorch/src/hooks/useClassifier.ts b/packages/react-native-executorch/src/hooks/useClassifier.ts
index 574b040ea8..6dbb15be4f 100644
--- a/packages/react-native-executorch/src/hooks/useClassifier.ts
+++ b/packages/react-native-executorch/src/hooks/useClassifier.ts
@@ -34,7 +34,7 @@ export function useClassifier<L>(config: ClassifierModel<L>, options?: { prevent
     error: downloadError || error,
     downloadProgress,
     localPath,
-    labels: config.classifierOpts.labels,
+    labels: config.opts.labels,
     classify: model?.classify,
     classifyWorklet: model?.classifyWorklet,
   };
diff --git a/packages/react-native-executorch/src/hooks/useSemanticSegmenter.ts b/packages/react-native-executorch/src/hooks/useSemanticSegmenter.ts
index 8140204e18..59d47330c1 100644
--- a/packages/react-native-executorch/src/hooks/useSemanticSegmenter.ts
+++ b/packages/react-native-executorch/src/hooks/useSemanticSegmenter.ts
@@ -2,7 +2,7 @@ import { useModel } from './useModel';
 import { useResourceDownload } from './useResourceDownload';
 import {
   createSemanticSegmenter,
-  type SemanticSegmentationModel,
+  type SemanticSegmenterModel,
 } from '../extensions/cv/tasks/semanticSegmentation';
 
 /**
@@ -22,7 +22,7 @@ import {
  * progress, and segmentation functions.
  */
 export function useSemanticSegmenter<L extends PropertyKey = string>(
-  config: SemanticSegmentationModel<L>,
+  config: SemanticSegmenterModel<L>,
   options?: { preventLoad?: boolean }
 ) {
   const { localPath, downloadProgress, downloadError } = useResourceDownload(
diff --git a/packages/react-native-executorch/src/models.ts b/packages/react-native-executorch/src/models.ts
index fc8e7a5e7d..4400ef2f20 100644
--- a/packages/react-native-executorch/src/models.ts
+++ b/packages/react-native-executorch/src/models.ts
@@ -1,7 +1,7 @@
 import type { ClassifierModel } from './extensions/cv/tasks/classification';
 import type { ObjectDetectorModel } from './extensions/cv/tasks/objectDetection';
 import type { StyleTransferModel } from './extensions/cv/tasks/styleTransfer';
-import type { SemanticSegmentationModel } from './extensions/cv/tasks/semanticSegmentation';
+import type { SemanticSegmenterModel } from './extensions/cv/tasks/semanticSegmentation';
 import type { KeypointDetectorModel } from './extensions/cv/tasks/keypointDetection';
 import type { InstanceSegmenterModel } from './extensions/cv/tasks/instanceSegmentation';
 import type { ImageEmbedderModel } from './extensions/cv/tasks/imageEmbedding';
@@ -38,21 +38,20 @@ const NEXT_VERSION_TAG = 'resolve/v0.10.0';
 const EFFICIENTNET_V2_S_OPTS = {
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
   labels: IMAGENET1K_LABELS,
 };
 const EFFICIENTNET_V2_S_XNNPACK_INT8: ClassifierModel<ImageNet1KLabel> = {
   modelPath: `${BASE_URL}-efficientnet-v2-s/${VERSION_TAG}/xnnpack/efficientnet_v2_s_xnnpack_int8.pte`,
-  classifierOpts: EFFICIENTNET_V2_S_OPTS,
+  opts: EFFICIENTNET_V2_S_OPTS,
 };
 const EFFICIENTNET_V2_S_XNNPACK_FP32: ClassifierModel<ImageNet1KLabel> = {
   modelPath: `${BASE_URL}-efficientnet-v2-s/${VERSION_TAG}/xnnpack/efficientnet_v2_s_xnnpack_fp32.pte`,
-  classifierOpts: EFFICIENTNET_V2_S_OPTS,
+  opts: EFFICIENTNET_V2_S_OPTS,
 };
 const EFFICIENTNET_V2_S_COREML_FP16: ClassifierModel<ImageNet1KLabel> = {
   modelPath: `${BASE_URL}-efficientnet-v2-s/${VERSION_TAG}/coreml/efficientnet_v2_s_coreml_fp16.pte`,
-  classifierOpts: EFFICIENTNET_V2_S_OPTS,
+  opts: EFFICIENTNET_V2_S_OPTS,
 };
 
 // =============================================================================
@@ -61,10 +60,8 @@ const EFFICIENTNET_V2_S_COREML_FP16: ClassifierModel<ImageNet1KLabel> = {
 const STYLE_TRANSFER_OPTS = {
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
-  outAlpha: 255.0,
-  outBeta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
+  outNormalizeOpts: { alpha: 255.0, beta: 0.0 },
   outInterpolation: 'lanczos' as const,
 };
 const STYLE_TRANSFER_CANDY_XNNPACK_FP32: StyleTransferModel = {
@@ -135,14 +132,13 @@ const STYLE_TRANSFER_UDNIE_COREML_FP32: StyleTransferModel = {
 // =============================================================================
 // Semantic Segmentation
 // =============================================================================
-const SELFIE_SEGMENTATION_XNNPACK_FP32: SemanticSegmentationModel<'background' | 'person'> = {
+const SELFIE_SEGMENTATION_XNNPACK_FP32: SemanticSegmenterModel<'background' | 'person'> = {
   modelPath: `${BASE_URL}-selfie-segmentation/${VERSION_TAG}/xnnpack/selfie_segmentation_xnnpack_fp32.pte`,
   opts: {
     labels: ['background', 'person'] as const,
     resizeMode: 'stretch',
     interpolation: 'linear',
-    alpha: 1 / 255.0,
-    beta: 0.0,
+    normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
     outInterpolation: 'lanczos',
   },
 };
@@ -152,13 +148,13 @@ const LRASPP_MOBILENET_V3_LARGE_OPTS = {
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
   outInterpolation: 'lanczos' as const,
-  ...IMAGENET_NORM,
+  normalizeOpts: IMAGENET_NORM,
 };
-const LRASPP_MOBILENET_V3_LARGE_XNNPACK_FP32: SemanticSegmentationModel<PascalVocLabel> = {
+const LRASPP_MOBILENET_V3_LARGE_XNNPACK_FP32: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-lraspp/${VERSION_TAG}/xnnpack/lraspp_mobilenet_v3_large_xnnpack_fp32.pte`,
   opts: LRASPP_MOBILENET_V3_LARGE_OPTS,
 };
-const LRASPP_MOBILENET_V3_LARGE_XNNPACK_INT8: SemanticSegmentationModel<PascalVocLabel> = {
+const LRASPP_MOBILENET_V3_LARGE_XNNPACK_INT8: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-lraspp/${VERSION_TAG}/xnnpack/lraspp_mobilenet_v3_large_xnnpack_int8.pte`,
   opts: LRASPP_MOBILENET_V3_LARGE_OPTS,
 };
@@ -168,29 +164,29 @@ const DEEPLAB_V3_OPTS = {
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
   outInterpolation: 'lanczos' as const,
-  ...IMAGENET_NORM,
+  normalizeOpts: IMAGENET_NORM,
 };
-const DEEPLAB_V3_RESNET50_XNNPACK_FP32: SemanticSegmentationModel<PascalVocLabel> = {
+const DEEPLAB_V3_RESNET50_XNNPACK_FP32: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-deeplab-v3/${NEXT_VERSION_TAG}/xnnpack/deeplab_v3_resnet50_xnnpack_fp32.pte`,
   opts: DEEPLAB_V3_OPTS,
 };
-const DEEPLAB_V3_RESNET50_XNNPACK_INT8: SemanticSegmentationModel<PascalVocLabel> = {
+const DEEPLAB_V3_RESNET50_XNNPACK_INT8: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-deeplab-v3/${NEXT_VERSION_TAG}/xnnpack/deeplab_v3_resnet50_xnnpack_int8.pte`,
   opts: DEEPLAB_V3_OPTS,
 };
-const DEEPLAB_V3_RESNET101_XNNPACK_FP32: SemanticSegmentationModel<PascalVocLabel> = {
+const DEEPLAB_V3_RESNET101_XNNPACK_FP32: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-deeplab-v3/${NEXT_VERSION_TAG}/xnnpack/deeplab_v3_resnet101_xnnpack_fp32.pte`,
   opts: DEEPLAB_V3_OPTS,
 };
-const DEEPLAB_V3_RESNET101_XNNPACK_INT8: SemanticSegmentationModel<PascalVocLabel> = {
+const DEEPLAB_V3_RESNET101_XNNPACK_INT8: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-deeplab-v3/${NEXT_VERSION_TAG}/xnnpack/deeplab_v3_resnet101_xnnpack_int8.pte`,
   opts: DEEPLAB_V3_OPTS,
 };
-const DEEPLAB_V3_MOBILENET_V3_LARGE_XNNPACK_FP32: SemanticSegmentationModel<PascalVocLabel> = {
+const DEEPLAB_V3_MOBILENET_V3_LARGE_XNNPACK_FP32: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-deeplab-v3/${NEXT_VERSION_TAG}/xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_fp32.pte`,
   opts: DEEPLAB_V3_OPTS,
 };
-const DEEPLAB_V3_MOBILENET_V3_LARGE_XNNPACK_INT8: SemanticSegmentationModel<PascalVocLabel> = {
+const DEEPLAB_V3_MOBILENET_V3_LARGE_XNNPACK_INT8: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-deeplab-v3/${NEXT_VERSION_TAG}/xnnpack/deeplab_v3_mobilenet_v3_large_xnnpack_int8.pte`,
   opts: DEEPLAB_V3_OPTS,
 };
@@ -200,21 +196,21 @@ const FCN_OPTS = {
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
   outInterpolation: 'lanczos' as const,
-  ...IMAGENET_NORM,
+  normalizeOpts: IMAGENET_NORM,
 };
-const FCN_RESNET50_XNNPACK_FP32: SemanticSegmentationModel<PascalVocLabel> = {
+const FCN_RESNET50_XNNPACK_FP32: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-fcn/${NEXT_VERSION_TAG}/xnnpack/fcn_resnet50_xnnpack_fp32.pte`,
   opts: FCN_OPTS,
 };
-const FCN_RESNET50_XNNPACK_INT8: SemanticSegmentationModel<PascalVocLabel> = {
+const FCN_RESNET50_XNNPACK_INT8: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-fcn/${NEXT_VERSION_TAG}/xnnpack/fcn_resnet50_xnnpack_int8.pte`,
   opts: FCN_OPTS,
 };
-const FCN_RESNET101_XNNPACK_FP32: SemanticSegmentationModel<PascalVocLabel> = {
+const FCN_RESNET101_XNNPACK_FP32: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-fcn/${NEXT_VERSION_TAG}/xnnpack/fcn_resnet101_xnnpack_fp32.pte`,
   opts: FCN_OPTS,
 };
-const FCN_RESNET101_XNNPACK_INT8: SemanticSegmentationModel<PascalVocLabel> = {
+const FCN_RESNET101_XNNPACK_INT8: SemanticSegmenterModel<PascalVocLabel> = {
   modelPath: `${BASE_URL}-fcn/${NEXT_VERSION_TAG}/xnnpack/fcn_resnet101_xnnpack_int8.pte`,
   opts: FCN_OPTS,
 };
@@ -227,8 +223,7 @@ const SSDLITE320_MOBILENET_V3_LARGE_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
   defaultConfidenceThreshold: 0.5,
   defaultIouThreshold: 0.55,
 };
@@ -250,7 +245,7 @@ const RFDETR_NANO_DETECTOR_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  ...IMAGENET_NORM,
+  normalizeOpts: IMAGENET_NORM,
   defaultConfidenceThreshold: 0.5,
   defaultIouThreshold: 0.55,
 };
@@ -268,8 +263,7 @@ const YOLO26_DETECTOR_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'letterbox' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
   defaultConfidenceThreshold: 0.25,
   defaultIouThreshold: 0.7,
 };
@@ -348,8 +342,7 @@ const BLAZEFACE_XNNPACK_FP32: KeypointDetectorModel<'xyxy', BlazeFaceLandmark> =
     boxFormat: 'xyxy',
     resizeMode: 'letterbox',
     interpolation: 'linear',
-    alpha: 1 / 127.5,
-    beta: -1.0,
+    normalizeOpts: { alpha: 1 / 127.5, beta: -1.0 },
     defaultIouThreshold: 0.3,
     defaultConfidenceThreshold: 0.75,
     landmarks: BLAZEFACE_LANDMARKS,
@@ -360,8 +353,7 @@ const YOLO26_POSE_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'letterbox' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
   defaultIouThreshold: 0.7,
   defaultConfidenceThreshold: 0.25,
   landmarks: COCO_LANDMARKS,
@@ -383,7 +375,7 @@ const RFDETR_KEYPOINT_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  ...IMAGENET_NORM,
+  normalizeOpts: IMAGENET_NORM,
   defaultIouThreshold: 0.55,
   defaultConfidenceThreshold: 0.5,
   landmarks: COCO_LANDMARKS,
@@ -409,8 +401,7 @@ const FASTSAM_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
   defaultConfidenceThreshold: 0.5,
   defaultIouThreshold: 0.9,
   defaultMaskThreshold: 0.5,
@@ -445,7 +436,7 @@ const RFDETR_NANO_SEG_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  ...IMAGENET_NORM,
+  normalizeOpts: IMAGENET_NORM,
   defaultConfidenceThreshold: 0.5,
   defaultIouThreshold: 0.55,
   defaultMaskThreshold: 0.5,
@@ -464,8 +455,7 @@ const YOLO26_SEG_OPTS = {
   boxFormat: 'xyxy' as const,
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
   defaultConfidenceThreshold: 0.25,
   defaultIouThreshold: 0.7,
   defaultMaskThreshold: 0.5,
@@ -584,8 +574,7 @@ const LFM2_5_EMBEDDING_350M_MLX_INT4: TextEmbedderModel = {
 const CLIP_IMAGE_EMBEDDINGS_OPTS = {
   resizeMode: 'stretch' as const,
   interpolation: 'linear' as const,
-  alpha: 1 / 255.0,
-  beta: 0.0,
+  normalizeOpts: { alpha: 1 / 255.0, beta: 0.0 },
 };
 const CLIP_VIT_BASE_PATCH32_IMAGE_XNNPACK_FP32: ImageEmbedderModel = {
   modelPath: `${BASE_URL}-clip-vit-base-patch32/${NEXT_VERSION_TAG}/xnnpack/clip_vit_base_patch32_image_xnnpack_fp32.pte`,