diff --git a/compiler/include/zamalang/Dialect/HLFHELinalg/IR/HLFHELinalgOps.td b/compiler/include/zamalang/Dialect/HLFHELinalg/IR/HLFHELinalgOps.td
index 4fe4fd156..f3ccbed2c 100644
--- a/compiler/include/zamalang/Dialect/HLFHELinalg/IR/HLFHELinalgOps.td
+++ b/compiler/include/zamalang/Dialect/HLFHELinalg/IR/HLFHELinalgOps.td
@@ -197,7 +197,7 @@ def MulEintIntOp : HLFHELinalg_Op<"mul_eint_int", [TensorBroadcastingRules, Tens
         // [7,8,9]   [3]   [21,24,27]
         //
         // The dimension #1 of operand #2 is stretched as it is equals to 1.
-        "HLFHELinalg.mul_eint_int(%a0, %a1)" : (tensor<3x4x!HLFHE.eint<4>>, tensor<3x1xi5>) -> tensor<3x3x!HLFHE.eint<4>>
+        "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<3x3x!HLFHE.eint<4>>, tensor<3x1xi5>) -> tensor<3x3x!HLFHE.eint<4>>
 
         // Returns the multiplication of a 3x3 matrix of encrypted integers and a 1x3 matrix (a line) of integers.
         //
@@ -206,10 +206,10 @@ def MulEintIntOp : HLFHELinalg_Op<"mul_eint_int", [TensorBroadcastingRules, Tens
         // [7,8,9]             [8,10,12]
         //
         // The dimension #2 of operand #2 is stretched as it is equals to 1.
-        "HLFHELinalg.mul_eint_int(%a0, %a1)" : (tensor<3x4x!HLFHE.eint<4>>, tensor<1x3xi5>) -> tensor<3x3x!HLFHE.eint<4>>
+        "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<3x3x!HLFHE.eint<4>>, tensor<1x3xi5>) -> tensor<3x3x!HLFHE.eint<4>>
 
         // Same behavior than the previous one, but as the dimension #2 is missing of operand #2.
-        "HLFHELinalg.mul_eint_int(%a0, %a1)" : (tensor<3x4x!HLFHE.eint<4>>, tensor<3xi5>) -> tensor<4x4x4x!HLFHE.eint<4>>
+        "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<3x3x!HLFHE.eint<4>>, tensor<3xi5>) -> tensor<3x3x!HLFHE.eint<4>>
 
         ```
     }];
diff --git a/compiler/lib/Conversion/HLFHETensorOpsToLinalg/TensorOpsToLinalg.cpp b/compiler/lib/Conversion/HLFHETensorOpsToLinalg/TensorOpsToLinalg.cpp
index ac842e5f5..b03ade271 100644
--- a/compiler/lib/Conversion/HLFHETensorOpsToLinalg/TensorOpsToLinalg.cpp
+++ b/compiler/lib/Conversion/HLFHETensorOpsToLinalg/TensorOpsToLinalg.cpp
@@ -276,6 +276,10 @@ void HLFHETensorOpsToLinalg::runOnFunction() {
       HLFHELinalgOpToLinalgGeneric<mlir::zamalang::HLFHELinalg::SubIntEintOp,
                                    mlir::zamalang::HLFHE::SubIntEintOp>>(
       &getContext());
+  patterns.insert<
+      HLFHELinalgOpToLinalgGeneric<mlir::zamalang::HLFHELinalg::MulEintIntOp,
+                                   mlir::zamalang::HLFHE::MulEintIntOp>>(
+      &getContext());
 
   if (mlir::applyPartialConversion(function, target, std::move(patterns))
           .failed())
diff --git a/compiler/tests/unittest/end_to_end_jit_encrypted_tensor.cc b/compiler/tests/unittest/end_to_end_jit_encrypted_tensor.cc
index 99a605f98..2aef85bc8 100644
--- a/compiler/tests/unittest/end_to_end_jit_encrypted_tensor.cc
+++ b/compiler/tests/unittest/end_to_end_jit_encrypted_tensor.cc
@@ -823,4 +823,222 @@ TEST(End2EndJit_HLFHELinalg, sub_int_eint_matrix_line_missing_dim) {
           << a0[i][j] - a1[0][j] << " got " << result[i][j] << "\n";
     }
   }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// HLFHELinalg mul_eint_int ///////////////////////////////////////////////////
+///////////////////////////////////////////////////////////////////////////////
+
+TEST(End2EndJit_HLFHELinalg, mul_eint_int_term_to_term) {
+  mlir::zamalang::CompilerEngine engine;
+  auto mlirStr = R"XXX(
+  // Returns the term to term multiplication of `%a0` with `%a1`
+  func @main(%a0: tensor<4x!HLFHE.eint<4>>, %a1: tensor<4xi5>) -> tensor<4x!HLFHE.eint<4>> {
+    %res = "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<4x!HLFHE.eint<4>>, tensor<4xi5>) -> tensor<4x!HLFHE.eint<4>>
+    return %res : tensor<4x!HLFHE.eint<4>>
+  }
+)XXX";
+  const uint8_t a0[4]{31, 6, 12, 9};
+  const uint8_t a1[4]{2, 3, 2, 3};
+
+  ASSERT_LLVM_ERROR(engine.compile(mlirStr, defaultV0Constraints()));
+
+  auto maybeArgument = engine.buildArgument();
+  ASSERT_LLVM_ERROR(maybeArgument.takeError());
+  auto argument = std::move(maybeArgument.get());
+  // Set the %a0 and %a1 argument
+  ASSERT_LLVM_ERROR(argument->setArg(0, (uint8_t *)a0, 4));
+  ASSERT_LLVM_ERROR(argument->setArg(1, (uint8_t *)a1, 4));
+  // Invoke the function
+  ASSERT_LLVM_ERROR(engine.invoke(*argument));
+  // Get and assert the result
+  uint64_t result[4];
+  ASSERT_LLVM_ERROR(argument->getResult(0, (uint64_t *)result, 4));
+  for (size_t i = 0; i < 4; i++) {
+    EXPECT_EQ(result[i], a0[i] * a1[i])
+        << "result differ at pos " << i << ", expect " << a0[i] * a1[i]
+        << " got " << result[i];
+  }
+}
+
+TEST(End2EndJit_HLFHELinalg, mul_eint_int_term_to_term_broadcast) {
+  mlir::zamalang::CompilerEngine engine;
+  auto mlirStr = R"XXX(
+  // Returns the term to term multiplication of `%a0` with `%a1`, where dimensions equals to one are stretched.
+  func @main(%a0: tensor<4x1x4x!HLFHE.eint<4>>, %a1: tensor<1x4x4xi5>) -> tensor<4x4x4x!HLFHE.eint<4>> {
+    %res = "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<4x1x4x!HLFHE.eint<4>>, tensor<1x4x4xi5>) -> tensor<4x4x4x!HLFHE.eint<4>>
+    return %res : tensor<4x4x4x!HLFHE.eint<4>>
+  }
+)XXX";
+  const uint8_t a0[4][1][4]{
+      {{1, 2, 3, 4}},
+      {{5, 6, 7, 8}},
+      {{9, 10, 11, 12}},
+      {{13, 14, 15, 16}},
+  };
+  const uint8_t a1[1][4][4]{
+      {
+          {1, 2, 0, 1},
+          {2, 0, 1, 2},
+          {0, 1, 2, 0},
+          {1, 2, 0, 1},
+      },
+  };
+
+  ASSERT_LLVM_ERROR(engine.compile(mlirStr, defaultV0Constraints()));
+
+  auto maybeArgument = engine.buildArgument();
+  ASSERT_LLVM_ERROR(maybeArgument.takeError());
+  auto argument = std::move(maybeArgument.get());
+  // Set the %a0 and %a1 argument
+  ASSERT_LLVM_ERROR(argument->setArg(0, (uint8_t *)a0, {4, 1, 4}));
+  ASSERT_LLVM_ERROR(argument->setArg(1, (uint8_t *)a1, {1, 4, 4}));
+  // Invoke the function
+  ASSERT_LLVM_ERROR(engine.invoke(*argument));
+  // Get and assert the result
+  uint64_t result[4][4][4];
+  ASSERT_LLVM_ERROR(argument->getResult(0, (uint64_t *)result, 4 * 4 * 4));
+  for (size_t i = 0; i < 4; i++) {
+    for (size_t j = 0; j < 4; j++) {
+      for (size_t k = 0; k < 4; k++) {
+        EXPECT_EQ(result[i][j][k], a0[i][0][k] * a1[0][j][k])
+            << "result differ at pos " << i << ", expect "
+            << a0[i][0][k] * a1[0][j][k] << " got " << result[i];
+      }
+    }
+  }
+}
+
+TEST(End2EndJit_HLFHELinalg, mul_eint_int_matrix_column) {
+  mlir::zamalang::CompilerEngine engine;
+  auto mlirStr = R"XXX(
+  // Returns the multiplication of a 3x3 matrix of encrypted integers and a 3x1 matrix (a column) of integers.
+  //
+  // [1,2,3]   [1]   [1,2,3]
+  // [4,5,6] * [2] = [8,10,18]
+  // [7,8,9]   [3]   [21,24,27]
+  //
+  // The dimension #1 of operand #2 is stretched as it is equals to 1.
+  func @main(%a0: tensor<3x3x!HLFHE.eint<4>>, %a1: tensor<3x1xi5>) -> tensor<3x3x!HLFHE.eint<4>> {
+    %res = "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<3x3x!HLFHE.eint<4>>, tensor<3x1xi5>) -> tensor<3x3x!HLFHE.eint<4>>
+    return %res : tensor<3x3x!HLFHE.eint<4>>
+  }
+)XXX";
+  const uint8_t a0[3][3]{
+      {1, 2, 3},
+      {4, 5, 6},
+      {7, 8, 9},
+  };
+  const uint8_t a1[3][1]{
+      {1},
+      {2},
+      {3},
+  };
+
+  ASSERT_LLVM_ERROR(engine.compile(mlirStr, defaultV0Constraints()));
+
+  auto maybeArgument = engine.buildArgument();
+  ASSERT_LLVM_ERROR(maybeArgument.takeError());
+  auto argument = std::move(maybeArgument.get());
+  // Set the %a0 and %a1 argument
+  ASSERT_LLVM_ERROR(argument->setArg(0, (uint8_t *)a0, {3, 3}));
+  ASSERT_LLVM_ERROR(argument->setArg(1, (uint8_t *)a1, {3, 1}));
+  // Invoke the function
+  ASSERT_LLVM_ERROR(engine.invoke(*argument));
+  // Get and assert the result
+  uint64_t result[3][3];
+  ASSERT_LLVM_ERROR(argument->getResult(0, (uint64_t *)result, 3 * 3));
+  for (size_t i = 0; i < 3; i++) {
+    for (size_t j = 0; j < 3; j++) {
+      EXPECT_EQ(result[i][j], a0[i][j] * a1[i][0])
+          << "result differ at pos " << i << ", expect " << a0[i][j] * a1[i][0]
+          << " got " << result[i];
+    }
+  }
+}
+
+TEST(End2EndJit_HLFHELinalg, mul_eint_int_matrix_line) {
+  mlir::zamalang::CompilerEngine engine;
+  auto mlirStr = R"XXX(
+  // Returns the multiplication of a 3x3 matrix of encrypted integers and a 1x3 matrix (a line) of integers.
+  //
+  // [1,2,3]             [2,4,6]
+  // [4,5,6] * [1,2,3] = [5,7,9]
+  // [7,8,9]             [8,10,12]
+  //
+  // The dimension #2 of operand #2 is stretched as it is equals to 1.
+  func @main(%a0: tensor<3x3x!HLFHE.eint<4>>, %a1: tensor<1x3xi5>) -> tensor<3x3x!HLFHE.eint<4>> {
+    %res = "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<3x3x!HLFHE.eint<4>>, tensor<1x3xi5>) -> tensor<3x3x!HLFHE.eint<4>>
+    return %res : tensor<3x3x!HLFHE.eint<4>>
+  }
+)XXX";
+  const uint8_t a0[3][3]{
+      {1, 2, 3},
+      {4, 5, 6},
+      {7, 8, 9},
+  };
+  const uint8_t a1[1][3]{
+      {1, 2, 3},
+  };
+
+  ASSERT_LLVM_ERROR(engine.compile(mlirStr, defaultV0Constraints()));
+
+  auto maybeArgument = engine.buildArgument();
+  ASSERT_LLVM_ERROR(maybeArgument.takeError());
+  auto argument = std::move(maybeArgument.get());
+  // Set the %a0 and %a1 argument
+  ASSERT_LLVM_ERROR(argument->setArg(0, (uint8_t *)a0, {3, 3}));
+  ASSERT_LLVM_ERROR(argument->setArg(1, (uint8_t *)a1, {1, 3}));
+  // Invoke the function
+  ASSERT_LLVM_ERROR(engine.invoke(*argument));
+  // Get and assert the result
+  uint64_t result[3][3];
+  ASSERT_LLVM_ERROR(argument->getResult(0, (uint64_t *)result, 3 * 3));
+  for (size_t i = 0; i < 3; i++) {
+    for (size_t j = 0; j < 3; j++) {
+      EXPECT_EQ(result[i][j], a0[i][j] * a1[0][j])
+          << "result differ at pos (" << i << "," << j << "), expect "
+          << a0[i][j] * a1[0][j] << " got " << result[i][j] << "\n";
+    }
+  }
+}
+
+TEST(End2EndJit_HLFHELinalg, mul_eint_int_matrix_line_missing_dim) {
+  mlir::zamalang::CompilerEngine engine;
+  auto mlirStr = R"XXX(
+  // Same behavior than the previous one, but as the dimension #2 of operand #2 is missing.
+  func @main(%a0: tensor<3x3x!HLFHE.eint<4>>, %a1: tensor<3xi5>) -> tensor<3x3x!HLFHE.eint<4>> {
+    %res = "HLFHELinalg.mul_eint_int"(%a0, %a1) : (tensor<3x3x!HLFHE.eint<4>>, tensor<3xi5>) -> tensor<3x3x!HLFHE.eint<4>>
+    return %res : tensor<3x3x!HLFHE.eint<4>>
+  }
+)XXX";
+  const uint8_t a0[3][3]{
+      {1, 2, 3},
+      {4, 5, 6},
+      {7, 8, 9},
+  };
+  const uint8_t a1[1][3]{
+      {1, 2, 3},
+  };
+
+  ASSERT_LLVM_ERROR(engine.compile(mlirStr, defaultV0Constraints()));
+
+  auto maybeArgument = engine.buildArgument();
+  ASSERT_LLVM_ERROR(maybeArgument.takeError());
+  auto argument = std::move(maybeArgument.get());
+  // Set the %a0 and %a1 argument
+  ASSERT_LLVM_ERROR(argument->setArg(0, (uint8_t *)a0, {3, 3}));
+  ASSERT_LLVM_ERROR(argument->setArg(1, (uint8_t *)a1, {3}));
+  // Invoke the function
+  ASSERT_LLVM_ERROR(engine.invoke(*argument));
+  // Get and assert the result
+  uint64_t result[3][3];
+  ASSERT_LLVM_ERROR(argument->getResult(0, (uint64_t *)result, 3 * 3));
+  for (size_t i = 0; i < 3; i++) {
+    for (size_t j = 0; j < 3; j++) {
+      EXPECT_EQ(result[i][j], a0[i][j] * a1[0][j])
+          << "result differ at pos (" << i << "," << j << "), expect "
+          << a0[i][j] * a1[0][j] << " got " << result[i][j] << "\n";
+    }
+  }
 }
\ No newline at end of file