diff --git a/tfjs-backend-webgl/src/kernel_utils/shared.ts b/tfjs-backend-webgl/src/kernel_utils/shared.ts
index b9a7a5a59f2..327a932a897 100644
--- a/tfjs-backend-webgl/src/kernel_utils/shared.ts
+++ b/tfjs-backend-webgl/src/kernel_utils/shared.ts
@@ -31,6 +31,7 @@ const {
   addImpl: addImplCPU,
   bincountImpl: bincountImplCPU,
   bincountReduceImpl: bincountReduceImplCPU,
+  bitwiseAndImpl: bitwiseAndImplCPU,
   castImpl: castImplCPU,
   ceilImpl: ceilImplCPU,
   concatImpl: concatImplCPU,
@@ -82,6 +83,7 @@ export {
   addImplCPU,
   bincountImplCPU,
   bincountReduceImplCPU,
+  bitwiseAndImplCPU,
   castImplCPU,
   ceilImplCPU,
   concatImplCPU,
diff --git a/tfjs-backend-webgl/src/kernels/BitwiseAnd.ts b/tfjs-backend-webgl/src/kernels/BitwiseAnd.ts
index 91e14f022b0..22f8a93557d 100644
--- a/tfjs-backend-webgl/src/kernels/BitwiseAnd.ts
+++ b/tfjs-backend-webgl/src/kernels/BitwiseAnd.ts
@@ -15,22 +15,64 @@
  * =============================================================================
  */
 
-import {BitwiseAnd, KernelConfig} from '@tensorflow/tfjs-core';
+import {BitwiseAnd, BitwiseAndInputs, env, KernelConfig, KernelFunc, TensorInfo, TypedArray} from '@tensorflow/tfjs-core';
+import {MathBackendWebGL} from '../backend_webgl';
+import {BinaryOpProgram} from '../binaryop_gpu';
+import {BinaryOpPackedProgram} from '../binaryop_packed_gpu';
+import {bitwiseAndImplCPU as cpuBitWiseAnd} from '../kernel_utils/shared';
 
-import {binaryKernelFunc} from '../kernel_utils/kernel_funcs_utils';
-import {bitwiseAndImplCPU as cpuBitwiseAnd} from '../kernel_utils/shared';
+export const BITWISEAND = `
+  int r = int(a.r) & int(b.r);
+  int g = int(a.g) & int(b.g);
+  int rb = int(a.b) & int(b.b);
+  int ra = int(a.a) & int(b.a);
+  return vec4(r, g, rb, ra);
+`;
 
-const BITWISEAND = 'return a & b;';
+export const BITWISEAND_UNPACKED = `
+  return float(int(a.r) & int(b.r));
+`;
 
-export const addKernelFunc = binaryKernelFunc({
-  opSnippet: BITWISEAND,
-  packedOpSnippet: BITWISEAND,
-  supportsComplex: true,
-  cpuKernelImpl: cpuBitwiseAnd
-});
+export function bitwiseAnd(args: {
+  inputs: BitwiseAndInputs,
+  backend: MathBackendWebGL,
+}): TensorInfo {
+  const {inputs, backend} = args;
+  const {a, b} = inputs;
+  const webglBackend = backend as MathBackendWebGL;
+  const shouldUsePackedProgram = env().getBool('WEBGL_PACK_BINARY_OPERATIONS');
+  const versionNumber = env().getNumber('WEBGL_VERSION');
+  if (versionNumber !== 2) {
+    throw new Error(
+        `Unsupported webgl version. Current webgl version: ${versionNumber}`);
+  }
 
-export const addConfig: KernelConfig = {
+  // The type of a and b are ensured to be `int` in core, therefore no need to
+  // consider other type situations.
+  if ((webglBackend.shouldExecuteOnCPU([a, b])) && cpuBitWiseAnd != null) {
+    const aVals = webglBackend.texData.get(a.dataId).values as TypedArray;
+    const bVals = webglBackend.texData.get(b.dataId).values as TypedArray;
+    const [outValues, outShape] =
+        cpuBitWiseAnd(a.shape, b.shape, aVals, bVals, a.dtype);
+
+    const out = webglBackend.makeTensorInfo(outShape, a.dtype);
+    const outData = webglBackend.texData.get(out.dataId);
+    outData.values = outValues;
+    return out;
+  }
+
+  let program: BinaryOpProgram|BinaryOpPackedProgram;
+  if (shouldUsePackedProgram) {
+    program = new BinaryOpPackedProgram(BITWISEAND, a.shape, b.shape, false);
+  } else {
+    program = new BinaryOpProgram(BITWISEAND_UNPACKED, a.shape, b.shape);
+  }
+
+  return webglBackend.runWebGLProgram(program, [a, b], a.dtype);
+}
+
+export const bitwiseAndConfig: KernelConfig = {
   kernelName: BitwiseAnd,
   backendName: 'webgl',
-  kernelFunc: addKernelFunc
+  kernelFunc: bitwiseAnd as unknown as KernelFunc
 };
diff --git a/tfjs-backend-webgl/src/register_all_kernels.ts b/tfjs-backend-webgl/src/register_all_kernels.ts
index 9f8e8f4ff39..42b1e0e9ae5 100644
--- a/tfjs-backend-webgl/src/register_all_kernels.ts
+++ b/tfjs-backend-webgl/src/register_all_kernels.ts
@@ -39,6 +39,7 @@ import {batchMatMulConfig} from './kernels/BatchMatMul';
 import {batchNormConfig} from './kernels/BatchNorm';
 import {batchToSpaceNDConfig} from './kernels/BatchToSpaceND';
 import {bincountConfig} from './kernels/Bincount';
+import {bitwiseAndConfig} from './kernels/BitwiseAnd';
 import {broadcastArgsConfig} from './kernels/BroadcastArgs';
 import {castConfig} from './kernels/Cast';
 import {ceilConfig} from './kernels/Ceil';
@@ -211,6 +212,7 @@ const kernelConfigs: KernelConfig[] = [
   batchNormConfig,
   batchToSpaceNDConfig,
   bincountConfig,
+  bitwiseAndConfig,
   broadcastArgsConfig,
   castConfig,
   ceilConfig,
diff --git a/tfjs-backend-webgl/src/setup_test.ts b/tfjs-backend-webgl/src/setup_test.ts
index a22acd98022..343a8e5e9af 100644
--- a/tfjs-backend-webgl/src/setup_test.ts
+++ b/tfjs-backend-webgl/src/setup_test.ts
@@ -36,7 +36,7 @@ const customInclude = (testName: string) => {
     'isBrowser: false', 'dilation gradient',
     'throws when index is out of bound',
     // otsu tests for threshold op is failing on windows
-    'method otsu', 'bitwiseAnd'
+    'method otsu'
   ];
   for (const subStr of toExclude) {
     if (testName.includes(subStr)) {