diff --git a/test/test_ops.py b/test/test_ops.py
index d16ce26ab2..067f6d2198 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -1095,17 +1095,10 @@ class TestOps(unittest.TestCase):
     helper_test_op([(4,4)], lambda x: x[:, 1:2][0:1])
     helper_test_op([(4,4)], lambda x: x[:, 1:2][:, 0:1])
 
-  @unittest.skipIf(Device.DEFAULT == "WEBGPU", "WEBGPU does not support nan/inf")
-  def test_max_nan(self):
-    n = Tensor([1, float("nan")]).max(ignore_nan=False).numpy()
+  @unittest.skip("this test is broken #862")
+  def test_max_inf(self):
+    n = Tensor([1, float("nan")]).max().numpy()
     assert math.isnan(n.item()), f"{n.item()} is not nan"
-    n = Tensor([float("nan"), 1]).max(ignore_nan=False).numpy()
-    assert math.isnan(n.item()), f"{n.item()} is not nan"
-
-  @unittest.skipIf(Device.DEFAULT == "WEBGPU", "WEBGPU does not support nan/inf")
-  def test_max_float4_nan(self):
-    n = Tensor(np.array([[1.0, 2.0, np.nan, 4.0], [5.0, 6.0, 7.0, 8.0]], dtype=np.float32)).max(ignore_nan=False).numpy()
-    assert math.isnan(n.item()), f"tinygrad max: {n.item()} is not nan"
 
   def test_inf_where(self):
     x = Tensor.full((3, 3), float("inf"))
diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index bd9995ae3a..e5c358ca73 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -381,8 +381,8 @@ class Tensor:
     return ret if keepdim else ret.reshape(shape=shape)
 
   def sum(self, axis=None, keepdim=False): return self._reduce(mlops.Sum, axis, keepdim)
+  def max(self, axis=None, keepdim=False): return self._reduce(mlops.Max, axis, keepdim)
   def min(self, axis=None, keepdim=False): return -((-self).max(axis=axis, keepdim=keepdim))
-  def max(self, axis=None, keepdim=False, ignore_nan=True): return self._reduce(mlops.Max, axis, keepdim) if ignore_nan else self._reduce(mlops.Max, axis, keepdim) + (self.isnan() * np.nan).sum()
 
   def mean(self, axis=None, keepdim=False):
     out = self.sum(axis=axis, keepdim=keepdim)
@@ -672,7 +672,6 @@ class Tensor:
   def element_size(self) -> int: return self.dtype.itemsize
   def nbytes(self) -> int: return self.numel() * self.element_size()
   def is_floating_point(self) -> bool: return dtypes.is_float(self.dtype)
-  def isnan(self) -> Tensor: return (self != self)
 
 # register functions to move between devices
 for device in Device._buffers: