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diff --git a/testing/web-platform/tests/webnn/validation_tests/gruCell.https.any.js b/testing/web-platform/tests/webnn/validation_tests/gruCell.https.any.js
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+// META: title=validation tests for WebNN API gruCell operation
+// META: global=window,dedicatedworker
+// META: script=../resources/utils_validation.js
+
+'use strict';
+
+const batchSize = 3, inputSize = 4, hiddenSize = 5;
+
+// Dimensions required of required inputs.
+const kValidInputDimensions = [batchSize, inputSize];
+const kValidWeightDimensions = [3 * hiddenSize, inputSize];
+const kValidRecurrentWeightDimensions = [3 * hiddenSize, hiddenSize];
+const kValidHiddenStateDimensions = [batchSize, hiddenSize];
+// Dimensions required of optional inputs.
+const kValidBiasDimensions = [3 * hiddenSize];
+const kValidRecurrentBiasDimensions = [3 * hiddenSize];
+// Dimensions required of required output.
+const kValidOutputDimensions = [batchSize, hiddenSize];
+
+// Example descriptors which are valid according to the above dimensions.
+const kExampleInputDescriptor = {
+  dataType: 'float32',
+  dimensions: kValidInputDimensions
+};
+const kExampleWeightDescriptor = {
+  dataType: 'float32',
+  dimensions: kValidWeightDimensions
+};
+const kExampleRecurrentWeightDescriptor = {
+  dataType: 'float32',
+  dimensions: kValidRecurrentWeightDimensions
+};
+const kExampleHiddenStateDescriptor = {
+  dataType: 'float32',
+  dimensions: kValidHiddenStateDimensions
+};
+const kExampleBiasDescriptor = {
+  dataType: 'float32',
+  dimensions: kValidBiasDimensions
+};
+const kExampleRecurrentBiasDescriptor = {
+  dataType: 'float32',
+  dimensions: kValidRecurrentBiasDimensions
+};
+const kExampleOutputDescriptor = {
+    dataType: 'float32',
+    dimensions: kValidOutputDimensions
+  };
+
+const tests = [
+    {
+        name: '[gruCell] Test with default options',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        output: kExampleOutputDescriptor
+    },
+    {
+        name: '[gruCell] Test with given options',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: {
+            bias: kExampleBiasDescriptor,
+            recurrentBias: kExampleRecurrentBiasDescriptor,
+            restAfter: true,
+            layout: 'rzn',
+            activations: ['sigmoid', 'relu']
+        },
+        output: kExampleOutputDescriptor
+    },
+    {
+        name: '[gruCell] Throw if hiddenSize equals to zero',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: 0
+    },
+    {
+        name: '[gruCell] Throw if hiddenSize is too large',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: 4294967295,
+    },
+    {
+        name:
+            '[gruCell] Throw if the data type of the inputs is not one of the floating point types',
+        input: { dataType: 'uint32', dimensions: kValidInputDimensions },
+        weight: { dataType: 'uint32', dimensions: kValidWeightDimensions },
+        recurrentWeight: {
+            dataType: 'uint32',
+            dimensions: kValidRecurrentWeightDimensions
+        },
+        hiddenState: {
+            dataType: 'uint32',
+            dimensions: kValidHiddenStateDimensions
+        },
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if the rank of input is not 2',
+        input: { dataType: 'float32', dimensions: [batchSize] },
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if the input.dimensions[1] is incorrect',
+        input: { dataType: 'float32', dimensions: [inputSize, inputSize] },
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name: '[gruCell] Throw if data type of weight is not one of the floating point types',
+        input: kExampleInputDescriptor,
+        weight: {
+            dataType: 'int8',
+            dimensions: [3 * hiddenSize, inputSize]
+        },
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name: '[gruCell] Throw if rank of weight is not 2',
+        input: kExampleInputDescriptor,
+        weight: {
+            dataType: 'float32',
+            dimensions: [3 * hiddenSize]
+        },
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name: '[gruCell] Throw if weight.dimensions[0] is not 3 * hiddenSize',
+        input: kExampleInputDescriptor,
+        weight: {
+            dataType: 'float32',
+            dimensions: [4 * hiddenSize, inputSize]
+        },
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name: '[gruCell] Throw if data type of recurrentWeight is not one of the floating point types',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: {
+            dataType: 'int32',
+            dimensions: [3 * hiddenSize, hiddenSize]
+        },
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if the rank of recurrentWeight is not 2',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight:
+            { dataType: 'float32', dimensions: [3 * hiddenSize] },
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if the recurrentWeight.dimensions is invalid',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight:
+            { dataType: 'float32', dimensions: [4 * hiddenSize, inputSize] },
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if data type of hiddenState is not one of the floating point types',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight:
+            kExampleRecurrentWeightDescriptor,
+        hiddenState: {
+            dataType: 'uint32',
+            dimensions: [batchSize, hiddenSize]
+        },
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if the rank of hiddenState is not 2',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight:
+            kExampleRecurrentWeightDescriptor,
+        hiddenState: {
+            dataType: 'float32',
+            dimensions: [hiddenSize]
+        },
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if the hiddenState.dimensions is invalid',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: {
+            dataType: 'float32',
+            dimensions: [batchSize, 3 * hiddenSize]
+        },
+        hiddenSize: hiddenSize
+    },
+    {
+        name:
+            '[gruCell] Throw if the size of options.activations is not 2',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: { activations: ['sigmoid', 'tanh', 'relu'] }
+    },
+    {
+        name:
+            '[gruCell] Throw if data type of options.bias is not one of the floating point types',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: { bias: { dataType: 'uint8', dimensions: [3 * hiddenSize] } }
+    },
+    {
+        name:
+            '[gruCell] Throw if the rank of options.bias is not 1',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: { bias: { dataType: 'float32', dimensions: [batchSize, 3 * hiddenSize] } }
+    },
+    {
+        name:
+            '[gruCell] Throw if options.bias.dimensions[0] is not 3 * hiddenSize',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: { bias: { dataType: 'float32', dimensions: [2 * hiddenSize] } }
+    },
+    {
+        name:
+            '[gruCell] Throw if data type of options.recurrentBias is not one of the floating point types',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: { recurrentBias: { dataType: 'int8', dimensions: [3 * hiddenSize] } }
+    },
+    {
+        name:
+            '[gruCell] Throw if the rank of options.recurrentBias is not 1',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: { recurrentBias: { dataType: 'float32', dimensions: [batchSize, 3 * hiddenSize] } }
+    },
+    {
+        name:
+            '[gruCell] Throw if options.recurrentBias.dimensions[0] is not 3 * hiddenSize',
+        input: kExampleInputDescriptor,
+        weight: kExampleWeightDescriptor,
+        recurrentWeight: kExampleRecurrentWeightDescriptor,
+        hiddenState: kExampleHiddenStateDescriptor,
+        hiddenSize: hiddenSize,
+        options: {
+            recurrentBias: { dataType: 'float16', dimensions: [4 * hiddenSize] }
+        }
+    }
+];
+
+tests.forEach(
+    test => promise_test(async t => {
+        const input = builder.input(
+            'input',
+            { dataType: test.input.dataType, dimensions: test.input.dimensions });
+        const weight = builder.input(
+            'weight',
+            { dataType: test.weight.dataType, dimensions: test.weight.dimensions });
+        const recurrentWeight = builder.input('recurrentWeight', {
+            dataType: test.recurrentWeight.dataType,
+            dimensions: test.recurrentWeight.dimensions
+        });
+        const hiddenState = builder.input('hiddenState', {
+            dataType: test.hiddenState.dataType,
+            dimensions: test.hiddenState.dimensions
+        });
+
+        const options = {};
+        if (test.options) {
+            if (test.options.bias) {
+                options.bias = builder.input('bias', {
+                    dataType: test.options.bias.dataType,
+                    dimensions: test.options.bias.dimensions
+                });
+            }
+            if (test.options.recurrentBias) {
+                options.bias = builder.input('recurrentBias', {
+                    dataType: test.options.recurrentBias.dataType,
+                    dimensions: test.options.recurrentBias.dimensions
+                });
+            }
+            if (test.options.resetAfter) {
+                options.resetAfter = test.options.resetAfter;
+            }
+            if (test.options.layout) {
+                options.layout = test.options.layout;
+            }
+            if (test.options.activations) {
+                options.activations = [];
+                test.options.activations.forEach(
+                    activation => options.activations.push(builder[activation]()));
+            }
+        }
+
+        if (test.output) {
+            const output = builder.gruCell(
+                input, weight, recurrentWeight, hiddenState, test.hiddenSize,
+                options);
+            assert_equals(output.dataType(), test.output.dataType);
+            assert_array_equals(output.shape(), test.output.dimensions);
+        } else {
+            assert_throws_js(
+                TypeError,
+                () => builder.gruCell(
+                    input, weight, recurrentWeight, hiddenState, test.hiddenSize,
+                    options));
+        }
+    }, test.name));
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const inputFromOtherBuilder =
+      otherBuilder.input('input', kExampleInputDescriptor);
+
+  const weight = builder.input('weight', kExampleWeightDescriptor);
+  const recurrentWeight =
+      builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
+  const hiddenState =
+      builder.input('hiddenState', kExampleHiddenStateDescriptor);
+  assert_throws_js(
+      TypeError,
+      () => builder.gruCell(
+          inputFromOtherBuilder, weight, recurrentWeight, hiddenState,
+          hiddenSize));
+}, '[gruCell] throw if input is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const weightFromOtherBuilder =
+      otherBuilder.input('weight', kExampleWeightDescriptor);
+
+  const input = builder.input('input', kExampleInputDescriptor);
+  const recurrentWeight =
+      builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
+  const hiddenState =
+      builder.input('hiddenState', kExampleHiddenStateDescriptor);
+  assert_throws_js(
+      TypeError,
+      () => builder.gruCell(
+          input, weightFromOtherBuilder, recurrentWeight, hiddenState,
+          hiddenSize));
+}, '[gruCell] throw if weight is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const recurrentWeightFromOtherBuilder =
+      otherBuilder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
+
+  const input = builder.input('input', kExampleInputDescriptor);
+  const weight = builder.input('weight', kExampleWeightDescriptor);
+  const hiddenState =
+      builder.input('hiddenState', kExampleHiddenStateDescriptor);
+  assert_throws_js(
+      TypeError,
+      () => builder.gruCell(
+          input, weight, recurrentWeightFromOtherBuilder, hiddenState,
+          hiddenSize));
+}, '[gruCell] throw if recurrentWeight is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const hiddenStateFromOtherBuilder =
+      otherBuilder.input('hiddenState', kExampleHiddenStateDescriptor);
+
+  const input = builder.input('input', kExampleInputDescriptor);
+  const weight = builder.input('weight', kExampleWeightDescriptor);
+  const recurrentWeight =
+      builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
+  assert_throws_js(
+      TypeError,
+      () => builder.gruCell(
+          input, weight, recurrentWeight, hiddenStateFromOtherBuilder,
+          hiddenSize));
+}, '[gruCell] throw if hiddenState is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const biasFromOtherBuilder =
+      otherBuilder.input('bias', kExampleBiasDescriptor);
+  const options = {bias: biasFromOtherBuilder};
+
+  const input = builder.input('input', kExampleInputDescriptor);
+  const weight = builder.input('weight', kExampleWeightDescriptor);
+  const recurrentWeight =
+      builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
+  const hiddenState =
+      builder.input('hiddenState', kExampleHiddenStateDescriptor);
+  assert_throws_js(
+      TypeError,
+      () => builder.gruCell(
+          input, weight, recurrentWeight, hiddenState, hiddenSize, options));
+}, '[gruCell] throw if bias option is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const recurrentBiasFromOtherBuilder =
+      otherBuilder.input('recurrentBias', kExampleRecurrentBiasDescriptor);
+  const options = {recurrentBias: recurrentBiasFromOtherBuilder};
+
+  const input = builder.input('input', kExampleInputDescriptor);
+  const weight = builder.input('weight', kExampleWeightDescriptor);
+  const recurrentWeight =
+      builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
+  const hiddenState =
+      builder.input('hiddenState', kExampleHiddenStateDescriptor);
+  assert_throws_js(
+      TypeError,
+      () => builder.gruCell(
+          input, weight, recurrentWeight, hiddenState, hiddenSize, options));
+}, '[gruCell] throw if recurrentBias option is from another builder');
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+  const activation = builder.clamp();
+  const activationFromOtherBuilder = otherBuilder.clamp();
+  const options = {activations: [activation, activationFromOtherBuilder]};
+
+  const input = builder.input('input', kExampleInputDescriptor);
+  const weight = builder.input('weight', kExampleWeightDescriptor);
+  const recurrentWeight =
+      builder.input('recurrentWeight', kExampleRecurrentWeightDescriptor);
+  const hiddenState =
+      builder.input('hiddenState', kExampleHiddenStateDescriptor);
+  assert_throws_js(
+      TypeError,
+      () => builder.gruCell(
+          input, weight, recurrentWeight, hiddenState, hiddenSize, options));
+}, '[gruCell] throw if any activation option is from another builder');