diff --git a/test/test_ops.py b/test/test_ops.py
index 6a975e8a79..952bf0930c 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -267,6 +267,7 @@ class TestOps(unittest.TestCase):
     helper_test_op([()], lambda x: torch.nn.functional.softsign(x), Tensor.softsign)
   def test_sigmoid(self):
     helper_test_op([(45,65)], lambda x: x.sigmoid(), Tensor.sigmoid)
+    helper_test_op([(45,65)], lambda x: x.sigmoid(), Tensor.sigmoid, a=100)
     helper_test_op([(45,65)], lambda x: x.sigmoid(), Tensor.sigmoid, a=-100)
     helper_test_op([()], lambda x: x.sigmoid(), Tensor.sigmoid, forward_only=True)
   def test_softplus(self):
@@ -274,9 +275,11 @@ class TestOps(unittest.TestCase):
     helper_test_op([()], lambda x: torch.nn.functional.softplus(x), Tensor.softplus, atol=1e-6, grad_atol=1e-6)
   def test_gelu(self):
     helper_test_op([(45,65)], lambda x: torch.nn.functional.gelu(x, approximate="tanh"), Tensor.gelu)
+    helper_test_op([(45,65)], lambda x: torch.nn.functional.gelu(x, approximate="tanh"), Tensor.gelu, a=100)
     helper_test_op([(45,65)], lambda x: torch.nn.functional.gelu(x, approximate="tanh"), Tensor.gelu, a=-100)
   def test_quick_gelu(self):
     helper_test_op([(45,65)], lambda x: x * torch.sigmoid(1.702 * x), Tensor.quick_gelu)
+    helper_test_op([(45,65)], lambda x: x * torch.sigmoid(1.702 * x), Tensor.quick_gelu, a=100)
     helper_test_op([(45,65)], lambda x: x * torch.sigmoid(1.702 * x), Tensor.quick_gelu, a=-100)
     helper_test_op([()], lambda x: x * torch.sigmoid(1.702 * x), Tensor.quick_gelu)
   def test_elu(self):
diff --git a/tinygrad/mlops.py b/tinygrad/mlops.py
index 87e4c4ab01..1bf04ff4f9 100644
--- a/tinygrad/mlops.py
+++ b/tinygrad/mlops.py
@@ -55,6 +55,9 @@ class Exp(Function):
   def backward(self, grad_output:LazyBuffer) -> LazyBuffer:
     return self.ret.binary_op(BinaryOps.MUL, grad_output)
 
+# NOTE: the implicit derivative of sigmoid is not stable
+# https://towardsdatascience.com/derivative-of-the-sigmoid-function-536880cf918e
+# TODO: have the backend automatically find this
 class Sigmoid(Function):
   __slots__ = "ret"
   def forward(self, x:LazyBuffer) -> LazyBuffer: