diff --git a/include/ck/library/utility/host_tensor_generator.hpp b/include/ck/library/utility/host_tensor_generator.hpp
index 274051da83..785f74a3c0 100644
--- a/include/ck/library/utility/host_tensor_generator.hpp
+++ b/include/ck/library/utility/host_tensor_generator.hpp
@@ -1,5 +1,5 @@
 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2025, Advanced Micro Devices, Inc. All rights reserved.
 
 #pragma once
 
@@ -81,6 +81,18 @@ struct GeneratorTensor_1<ck::f4_t>
     }
 };
 
+template <>
+struct GeneratorTensor_1<ck::f4x2_pk_t>
+{
+    float value = 1.0;
+
+    template <typename... Is>
+    ck::f4x2_pk_t operator()(Is...)
+    {
+        return ck::f4x2_pk_t{ck::type_convert<ck::f4x2_t>(ck::float2_t{value, value})};
+    }
+};
+
 template <>
 struct GeneratorTensor_1<int8_t>
 {
@@ -209,6 +221,21 @@ struct GeneratorTensor_2<ck::f4_t>
     }
 };
 
+template <>
+struct GeneratorTensor_2<ck::f4x2_pk_t>
+{
+    int min_value = 0;
+    int max_value = 1;
+
+    template <typename... Is>
+    ck::f4x2_pk_t operator()(Is...)
+    {
+        float tmp0 = (std::rand() % (max_value - min_value)) + min_value;
+        float tmp1 = (std::rand() % (max_value - min_value)) + min_value;
+        return ck::f4x2_pk_t{ck::type_convert<ck::f4x2_t>(ck::float2_t{tmp0, tmp1})};
+    }
+};
+
 template <typename T>
 struct GeneratorTensor_3
 {
@@ -296,6 +323,25 @@ struct GeneratorTensor_3<ck::f4_t>
     }
 };
 
+template <>
+struct GeneratorTensor_3<ck::f4x2_pk_t>
+{
+    float min_value = 0;
+    float max_value = 1;
+
+    template <typename... Is>
+    ck::f4x2_pk_t operator()(Is...)
+    {
+        float tmp0 = float(std::rand()) / float(RAND_MAX);
+        float tmp1 = float(std::rand()) / float(RAND_MAX);
+
+        float fp32_tmp0 = min_value + tmp0 * (max_value - min_value);
+        float fp32_tmp1 = min_value + tmp1 * (max_value - min_value);
+
+        return ck::f4x2_pk_t{ck::type_convert<ck::f4x2_t>(ck::float2_t{fp32_tmp0, fp32_tmp1})};
+    }
+};
+
 template <typename T>
 struct GeneratorTensor_4
 {
diff --git a/test/mx_mfma_op/mx_mfma_op.cpp b/test/mx_mfma_op/mx_mfma_op.cpp
index cafd5179f4..f76e8437d7 100644
--- a/test/mx_mfma_op/mx_mfma_op.cpp
+++ b/test/mx_mfma_op/mx_mfma_op.cpp
@@ -127,7 +127,7 @@ TEST(MXMFMA, MXFP8MFMA32x32x64)
 
 TEST(MXMFMA, MXFP4MFMA16x16x128)
 {
-    auto AB_init = 7;
+    auto AB_init = 4;
     auto pass =
         run_mxmfma_test<f4x2_pk_t, f4x2_pk_t, float, ck::MFMA_F8F6F4::SCALE_F32_16x16x128>(AB_init);
     EXPECT_TRUE(pass);
@@ -135,7 +135,7 @@ TEST(MXMFMA, MXFP4MFMA16x16x128)
 
 TEST(MXMFMA, MXFP4MFMA32x32x64)
 {
-    auto AB_init = 7;
+    auto AB_init = 4;
     auto pass =
         run_mxmfma_test<f4x2_pk_t, f4x2_pk_t, half_t, ck::MFMA_F8F6F4::SCALE_F32_32x32x64>(AB_init);
     EXPECT_TRUE(pass);
diff --git a/test/mx_mfma_op/mx_mfma_op.hpp b/test/mx_mfma_op/mx_mfma_op.hpp
index fee1047a8d..d46f234f98 100644
--- a/test/mx_mfma_op/mx_mfma_op.hpp
+++ b/test/mx_mfma_op/mx_mfma_op.hpp
@@ -997,7 +997,6 @@ struct TestMXMFMA
             b_n_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{-2.0, 2.0});
             b_scales.GenerateTensorValue(GeneratorTensor_2<ScaleType>{126, 129});
             break;
-
         case 3:
             // expect small round off errors
             a_m_k.GenerateTensorValue(GeneratorTensor_4<ADataType>(0, 1));
@@ -1007,6 +1006,14 @@ struct TestMXMFMA
             b_scales.GenerateTensorValue(
                 GeneratorTensor_2<ScaleType>{126, 129}); //  scales: {0.5, 1, 2}
             break;
+        case 4:
+            a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{-1., 1.});
+            a_scales.GenerateTensorValue(
+                GeneratorTensor_2<ScaleType>{126, 129}); // scales: {0.5, 1, 2}
+            b_n_k.GenerateTensorValue(GeneratorTensor_3<BDataType>{-1., 1.});
+            b_scales.GenerateTensorValue(
+                GeneratorTensor_2<ScaleType>{126, 129}); //  scales: {0.5, 1, 2}
+            break;
         default:
             // all initial values are representable in FP8, BF8
             a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 6}); // Z[-5,5]