diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
index b5fda8cf6cf1f..d6d065bf9f809 100644
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -1021,6 +1021,9 @@ def atan2_(self, other):
 
     def fmin(self, other):
         return torch_frontend.fmin(self, other)
+    
+    def fmax(self,other):
+        return torch_frontend.fmax(self,other)
 
     @with_unsupported_dtypes({"2.0.1 and below": ("float16", "complex")}, "torch")
     def trunc(self):
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index 3ff4e9866e302..67975c6da83b6 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -7828,6 +7828,44 @@ def test_torch_fmin(
         on_device=on_device,
     )
 
+#fmax
+
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="fmax",
+    dtype_and_x= helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        num_arrays=2,
+    ),
+)
+def test_torch_fmax(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "other": x[1],
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
 
 # count_nonzero
 @handle_frontend_method(