diff --git a/src/ntops/kernels/eq.py b/src/ntops/kernels/eq.py
new file mode 100644
index 0000000..2f0c0bb
--- /dev/null
+++ b/src/ntops/kernels/eq.py
@@ -0,0 +1,17 @@
+import functools
+
+import ninetoothed
+from ninetoothed import Tensor
+
+from ntops.kernels.element_wise import arrangement
+
+
+def application(input, other, output):
+    output = input == other  # noqa: F841
+
+
+@functools.cache
+def make(ndim):
+    tensors = (Tensor(ndim), Tensor(ndim), Tensor(ndim))
+
+    return ninetoothed.make(arrangement, application, tensors)
diff --git a/src/ntops/torch.py b/src/ntops/torch.py
index 9a4c895..4b39273 100644
--- a/src/ntops/torch.py
+++ b/src/ntops/torch.py
@@ -6,6 +6,7 @@
 import ntops.kernels.bmm
 import ntops.kernels.cos
 import ntops.kernels.div
+import ntops.kernels.eq
 import ntops.kernels.exp
 import ntops.kernels.gelu
 import ntops.kernels.mm
@@ -99,6 +100,17 @@ def exp(input, *, out=None):
     return out
 
 
+def eq(input, other, *, out=None):
+    if out is None:
+        out = torch.empty_like(input)
+
+    kernel = ntops.kernels.eq.make(input.ndim)
+
+    kernel(input, other, out)
+
+    return out
+
+
 def gelu(input, approximate="none"):
     output = torch.empty_like(input)
 
diff --git a/tests/test_eq.py b/tests/test_eq.py
new file mode 100644
index 0000000..6a58ffc
--- /dev/null
+++ b/tests/test_eq.py
@@ -0,0 +1,20 @@
+import pytest
+import torch
+
+import ntops.torch
+from tests.skippers import skip_if_cuda_not_available
+from tests.utils import generate_arguments
+
+
+@skip_if_cuda_not_available
+@pytest.mark.parametrize(*generate_arguments())
+def test_cuda(shape, dtype, atol, rtol):
+    device = "cuda"
+
+    input = torch.randn(shape, dtype=dtype, device=device)
+    other = torch.randn(shape, dtype=dtype, device=device)
+
+    ninetoothed_output = ntops.torch.eq(input, other)
+    reference_output = torch.eq(input, other)
+
+    assert torch.equal(ninetoothed_output, reference_output)