diff --git a/src/TensorFlowNET.Core/NumPy/NumPy.Sorting.Searching.Counting.cs b/src/TensorFlowNET.Core/NumPy/NumPy.Sorting.Searching.Counting.cs
index 5182d5726..4cad36e0b 100644
--- a/src/TensorFlowNET.Core/NumPy/NumPy.Sorting.Searching.Counting.cs
+++ b/src/TensorFlowNET.Core/NumPy/NumPy.Sorting.Searching.Counting.cs
@@ -13,6 +13,10 @@ public partial class np
         public static NDArray argmax(NDArray a, Axis? axis = null)
             => new NDArray(math_ops.argmax(a, axis ?? 0));
 
+        [AutoNumPy]
+        public static NDArray argmin(NDArray a, Axis? axis = null)
+            => new NDArray(math_ops.argmin(a, axis ?? 0));
+
         [AutoNumPy]
         public static NDArray argsort(NDArray a, Axis? axis = null)
             => new NDArray(sort_ops.argsort(a, axis: axis ?? -1));
diff --git a/src/TensorFlowNET.Core/NumPy/NumPy.Statistics.cs b/src/TensorFlowNET.Core/NumPy/NumPy.Statistics.cs
index 5d86b1b39..bce16ec9f 100644
--- a/src/TensorFlowNET.Core/NumPy/NumPy.Statistics.cs
+++ b/src/TensorFlowNET.Core/NumPy/NumPy.Statistics.cs
@@ -10,10 +10,10 @@ namespace Tensorflow.NumPy
     public partial class np
     {
         [AutoNumPy]
-        public static NDArray amin(NDArray x, int axis = 0) => new NDArray(tf.arg_min(x, axis));
+        public static NDArray amin(NDArray x, int axis = 0) => new NDArray(tf.min(x, axis));
 
         [AutoNumPy]
-        public static NDArray amax(NDArray x, int axis = 0) => new NDArray(tf.math.argmax(x, axis));
+        public static NDArray amax(NDArray x, int axis = 0) => new NDArray(tf.max(x, axis));
 
         [AutoNumPy]
         public static NDArray average(NDArray a, int axis = -1, NDArray? weights = null, bool returned = false)
diff --git a/src/TensorFlowNET.Core/Operations/math_ops.cs b/src/TensorFlowNET.Core/Operations/math_ops.cs
index 092137bf2..e77df702f 100644
--- a/src/TensorFlowNET.Core/Operations/math_ops.cs
+++ b/src/TensorFlowNET.Core/Operations/math_ops.cs
@@ -77,6 +77,9 @@ public static Tensor add_n(Tensor[] inputs, string name = null)
         public static Tensor argmax(Tensor input, Axis dimension, TF_DataType output_type = TF_DataType.TF_INT64, string name = null)
             => gen_math_ops.arg_max(input, dimension, output_type: output_type, name: name);
 
+        public static Tensor argmin(Tensor input, Axis dimension, TF_DataType output_type = TF_DataType.TF_INT64, string name = null)
+            => gen_math_ops.arg_min(input, dimension, output_type: output_type, name: name);
+
         public static Tensor round(Tensor x, string name = null)
         {
             x = ops.convert_to_tensor(x, name: "x");