diff --git a/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js b/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
index 75893eb34cb2..20c050d7bd8e 100644
--- a/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
+++ b/testing/web-platform/tests/webnn/conformance_tests/softmax.https.any.js
@@ -10,4 +10,4 @@
 
 // https://webmachinelearning.github.io/webnn/#api-mlgraphbuilder-softmax
 
-runWebNNConformanceTests('softmax', buildOperationWithSingleInput);
+runWebNNConformanceTests('softmax', buildSoftmax);
diff --git a/testing/web-platform/tests/webnn/resources/test_data/softmax.json b/testing/web-platform/tests/webnn/resources/test_data/softmax.json
index ebb12114fc6e..cbe868ac1dee 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/softmax.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/softmax.json
@@ -198,6 +198,93 @@
         ],
         "type": "float32"
       }
+    },
+    {
+      "name": "softmax float32 3D constant tensor",
+      "inputs": {
+        "x": {
+          "shape": [1, 3, 4],
+          "data": [
+            0.4301910996437073,
+            0.5471914410591125,
+            -1.1637765169143677,
+            0.18390046060085297,
+            0.583903968334198,
+            0.17356790602207184,
+            0.5397239923477173,
+            -0.9535139799118042,
+            -0.5920282602310181,
+            -0.17344485223293304,
+            0.14395014941692352,
+            -0.37920907139778137
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "axis": 1,
+      "expected": {
+        "name": "output",
+        "shape": [1, 3, 4],
+        "data": [
+          0.39589041471481323,
+          0.45983806252479553,
+          0.09812675416469574,
+          0.529077410697937,
+          0.4616699814796448,
+          0.31647709012031555,
+          0.5390242338180542,
+          0.16964708268642426,
+          0.142439603805542,
+          0.22368484735488892,
+          0.36284899711608887,
+          0.3012755215167999
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "softmax float32 4D tensor",
+      "inputs": {
+        "x": {
+          "shape": [3, 4, 1, 1],
+          "data": [
+            0.4301910996437073,
+            0.5471914410591125,
+            -1.1637765169143677,
+            0.18390046060085297,
+            0.583903968334198,
+            0.17356790602207184,
+            0.5397239923477173,
+            -0.9535139799118042,
+            -0.5920282602310181,
+            -0.17344485223293304,
+            0.14395014941692352,
+            -0.37920907139778137
+          ],
+          "type": "float32"
+        }
+      },
+      "axis": 1,
+      "expected": {
+        "name": "output",
+        "shape": [3, 4, 1, 1],
+        "data": [
+          0.3216537833213806,
+          0.3615773916244507,
+          0.06533370912075043,
+          0.25143513083457947,
+          0.35271573066711426,
+          0.23400123417377472,
+          0.33747196197509766,
+          0.07581108063459396,
+          0.17110128700733185,
+          0.26004093885421753,
+          0.3571779429912567,
+          0.2116798311471939
+        ],
+        "type": "float32"
+      }
     }
   ]
 }
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/utils.js b/testing/web-platform/tests/webnn/resources/utils.js
index 3cfcf579a50e..363341bec8f3 100644
--- a/testing/web-platform/tests/webnn/resources/utils.js
+++ b/testing/web-platform/tests/webnn/resources/utils.js
@@ -785,6 +785,20 @@ const buildSlice = (operationName, builder, resources) => {
   return namedOutputOperand;
 };
 
+const buildSoftmax = (operationName, builder, resources) => {
+  // MLOperand softmax(MLOperand input, [EnforceRange] unsigned long axis);
+  const namedOutputOperand = {};
+  const inputOperand = createSingleInputOperand(builder, resources);
+  if (resources.axis !== undefined) {
+    // invoke builder.softmax(input, axis)
+    namedOutputOperand[resources.expected.name] = builder[operationName](inputOperand, resources.axis);
+  } else {
+    // invoke builder.softmax(input)
+    namedOutputOperand[resources.expected.name] = builder[operationName](inputOperand);
+  }
+  return namedOutputOperand;
+};
+
 const buildSplit = (operationName, builder, resources) => {
   // sequence<MLOperand> split(MLOperand input,
   //                           (unsigned long or sequence<unsigned long>) splits,
diff --git a/testing/web-platform/tests/webnn/validation_tests/softmax.https.any.js b/testing/web-platform/tests/webnn/validation_tests/softmax.https.any.js
index 68891b27d880..a75878307f62 100644
--- a/testing/web-platform/tests/webnn/validation_tests/softmax.https.any.js
+++ b/testing/web-platform/tests/webnn/validation_tests/softmax.https.any.js
@@ -4,4 +4,97 @@
 
 'use strict';
 
-validateInputFromAnotherBuilder('softmax');
+const tests_without_axis = [
+    {
+        name: '[softmax] Test building Softmax with float32 input without axis.',
+        input: { dataType: 'float32', dimensions: [4, 3] },
+        output: { dataType: 'float32', dimensions: [4, 3] }
+    },
+    {
+        name: '[softmax] Test building Softmax with float16 input without axis.',
+        input: { dataType: 'float16', dimensions: [3, 5] },
+        output: { dataType: 'float16', dimensions: [3, 5] }
+    },
+    {
+        name: '[softmax] Throw if the input is not a non-floating point data.',
+        input: { dataType: 'int32', dimensions: [3, 2] }
+    },
+    {
+        name: '[softmax] Throw if the input dimensions is not 2.',
+        input: { dataType: 'float32', dimensions: [1, 4, 3] }
+    }
+];
+
+tests_without_axis.forEach(test =>
+    promise_test(async t => {
+        let input = builder.input(
+            `input`, { dataType: test.input.dataType, dimensions: test.input.dimensions }
+        );
+        if (test.output) {
+            const output = builder.softmax(input);
+            assert_equals(output.dataType(), test.output.dataType);
+            assert_array_equals(output.shape(), test.output.dimensions);
+        } else {
+            assert_throws_js(TypeError, () => builder.softmax(input));
+        }
+    }, test.name)
+);
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+    const operandDescriptor = { dataType: 'float32', dimensions: [2, 3] };
+    const inputFromOtherBuilder = otherBuilder.input('input', operandDescriptor);
+
+    assert_throws_js(
+        TypeError,
+        () => builder.softmax(inputFromOtherBuilder));
+}, '[softmax without axis] throw if any input is from another builder');
+
+const tests = [
+    {
+        name: '[softmax] Test building Softmax with float32 input.',
+        input: { dataType: 'float32', dimensions: [4, 4, 3] },
+        axis: 1,
+        output: { dataType: 'float32', dimensions: [4, 4, 3] }
+    },
+    {
+        name: '[softmax] Test building Softmax with float16 input.',
+        input: { dataType: 'float16', dimensions: [3, 1, 5, 2] },
+        axis: 2,
+        output: { dataType: 'float16', dimensions: [3, 1, 5, 2] }
+    },
+    {
+        name: '[softmax] Throw if the input is not a non-floating-point data.',
+        input: { dataType: 'int32', dimensions: [3, 1, 5, 2] },
+        axis: 3
+    },
+    {
+        name: '[softmax] Throw if the axis is greater than input rank - 1.',
+        input: { dataType: 'float16', dimensions: [3, 1, 5, 2] },
+        axis: 4
+    }
+];
+
+tests.forEach(test =>
+    promise_test(async t => {
+        let input = builder.input(
+            `input`, { dataType: test.input.dataType, dimensions: test.input.dimensions }
+        );
+        if (test.output) {
+            const output = builder.softmax(input, test.axis);
+            assert_equals(output.dataType(), test.output.dataType);
+            assert_array_equals(output.shape(), test.output.dimensions);
+        } else {
+            assert_throws_js(TypeError, () => builder.softmax(input, test.axis));
+        }
+    }, test.name)
+);
+
+multi_builder_test(async (t, builder, otherBuilder) => {
+    const operandDescriptor = { dataType: 'float32', dimensions: [1, 2, 3] };
+    const inputFromOtherBuilder = otherBuilder.input('input', operandDescriptor);
+    const axis = 1;
+
+    assert_throws_js(
+        TypeError,
+        () => builder.softmax(inputFromOtherBuilder, axis));
+}, '[softmax] throw if any input is from another builder');