diff --git a/src/Nncase.Importer/Onnx/Reduce.cs b/src/Nncase.Importer/Onnx/Reduce.cs
index e3baa6822e..63b8432175 100644
--- a/src/Nncase.Importer/Onnx/Reduce.cs
+++ b/src/Nncase.Importer/Onnx/Reduce.cs
@@ -11,12 +11,12 @@ namespace Nncase.Importer
 {
     public partial class OnnxImporter
     {
-        private Expr VisitReduce(in NodeProto op, ReduceOp reduceOp, float initValue)
+        private Expr VisitReduce(in NodeProto op, ReduceOp reduceOp, Expr initValue)
         {
             return ReduceCore(op, reduceOp, initValue, expr => expr);
         }
 
-        private Expr ReduceCore(in NodeProto op, ReduceOp reduceOp, float initValue, Func<Expr, Expr> f)
+        private Expr ReduceCore(in NodeProto op, ReduceOp reduceOp, Expr initValue, Func<Expr, Expr> f)
         {
             var input = GetInputExpr(op, 0);
             Expr axis;
@@ -51,6 +51,12 @@ private Expr ReduceCore(in NodeProto op, ReduceOp reduceOp, float initValue, Fun
                 var x when x == ReduceOp.Max && input.CheckedDataType == DataTypes.Int32 => F.Tensors.Reduce(reduceOp, f(input), axis, int.MinValue, keepDims),
                 var x when x == ReduceOp.Min && input.CheckedDataType == DataTypes.Int64 => F.Tensors.Reduce(reduceOp, f(input), axis, long.MaxValue, keepDims),
                 var x when x == ReduceOp.Min && input.CheckedDataType == DataTypes.Int32 => F.Tensors.Reduce(reduceOp, f(input), axis, int.MaxValue, keepDims),
+                var x when x == ReduceOp.Max && input.CheckedDataType == DataTypes.Float32 => F.Tensors.Reduce(reduceOp, f(input), axis, float.MinValue, keepDims),
+                var x when x == ReduceOp.Max && input.CheckedDataType == DataTypes.Float16 => F.Tensors.Reduce(reduceOp, f(input), axis, Half.MinValue, keepDims),
+                var x when x == ReduceOp.Max && input.CheckedDataType == DataTypes.BFloat16 => F.Tensors.Reduce(reduceOp, f(input), axis, BFloat16.RoundToBFloat16(float.MinValue), keepDims),
+                var x when x == ReduceOp.Min && input.CheckedDataType == DataTypes.Float32 => F.Tensors.Reduce(reduceOp, f(input), axis, float.MaxValue, keepDims),
+                var x when x == ReduceOp.Min && input.CheckedDataType == DataTypes.Float16 => F.Tensors.Reduce(reduceOp, f(input), axis, Half.MaxValue, keepDims),
+                var x when x == ReduceOp.Min && input.CheckedDataType == DataTypes.BFloat16 => F.Tensors.Reduce(reduceOp, f(input), axis, BFloat16.RoundToBFloat16(float.MaxValue), keepDims),
                 _ => F.Tensors.Reduce(reduceOp, f(input), axis, F.Tensors.Cast(initValue, input.CheckedDataType), keepDims),
             };
         }
diff --git a/src/Nncase.Importer/Onnx/ReduceWindow2D.cs b/src/Nncase.Importer/Onnx/ReduceWindow2D.cs
index 07273a38ae..25bcb23873 100644
--- a/src/Nncase.Importer/Onnx/ReduceWindow2D.cs
+++ b/src/Nncase.Importer/Onnx/ReduceWindow2D.cs
@@ -14,7 +14,7 @@ namespace Nncase.Importer
     public partial class OnnxImporter
     {
         // isGlobal used for GlobalXXXPool
-        private Expr VisitReduceWindow2D(in NodeProto op, ReduceOp reduceOp, float initValue, bool isGlobal = false)
+        private Expr VisitReduceWindow2D(in NodeProto op, ReduceOp reduceOp, Expr initValue, bool isGlobal = false)
         {
             // auto_pad had been DEPRECATED
             var input = GetInputExpr(op, 0);
diff --git a/tests/importer/onnx_/basic/test_reduce.py b/tests/importer/onnx_/basic/test_reduce.py
index 2404899474..879d7f9a7b 100644
--- a/tests/importer/onnx_/basic/test_reduce.py
+++ b/tests/importer/onnx_/basic/test_reduce.py
@@ -22,7 +22,7 @@
 import numpy as np
 
 
-def _make_module(in_shape, reduce_op, axes, keepdims, op_version):
+def _make_module(in_shape, in_datatype, reduce_op, axes, keepdims, op_version):
     inputs = []
     outputs = []
     initializers = []
@@ -30,14 +30,14 @@ def _make_module(in_shape, reduce_op, axes, keepdims, op_version):
     nodes = []
 
     # input
-    input = helper.make_tensor_value_info('input', TensorProto.FLOAT, in_shape)
+    input = helper.make_tensor_value_info('input', in_datatype, in_shape)
     inputs.append('input')
 
     # output
     kd = 1 if keepdims is None else keepdims
     data = np.ones(in_shape)
     out_shape = np.prod(data, axis=tuple(axes), keepdims=kd).shape
-    output = helper.make_tensor_value_info('output', TensorProto.FLOAT, out_shape)
+    output = helper.make_tensor_value_info('output', in_datatype, out_shape)
     outputs.append('output')
 
     # axes
@@ -73,6 +73,11 @@ def _make_module(in_shape, reduce_op, axes, keepdims, op_version):
     [1, 3, 16, 16]
 ]
 
+in_datatypes = [
+    TensorProto.FLOAT,
+    TensorProto.FLOAT16
+]
+
 reduce_ops = [
     'ReduceMax',
     'ReduceMean',
@@ -108,13 +113,14 @@ def _make_module(in_shape, reduce_op, axes, keepdims, op_version):
 
 
 @pytest.mark.parametrize('in_shape', in_shapes)
+@pytest.mark.parametrize('in_datatype', in_datatypes)
 @pytest.mark.parametrize('reduce_op', reduce_ops)
 @pytest.mark.parametrize('axes', axes_list)
 @pytest.mark.parametrize('keepdims', keepdims_lists)
 @pytest.mark.parametrize('op_version', op_version_lists)
-def test_reduce(in_shape, reduce_op, axes, keepdims, request, op_version):
+def test_reduce(in_shape, in_datatype, reduce_op, axes, keepdims, request, op_version):
     if len(axes) <= len(in_shape):
-        model_def = _make_module(in_shape, reduce_op, axes, keepdims, op_version)
+        model_def = _make_module(in_shape, in_datatype, reduce_op, axes, keepdims, op_version)
 
         runner = OnnxTestRunner(request.node.name)
         model_file = runner.from_onnx_helper(model_def)