diff --git a/pytensor/link/numba/dispatch/nlinalg.py b/pytensor/link/numba/dispatch/nlinalg.py
index 63115e1926..860560d0a6 100644
--- a/pytensor/link/numba/dispatch/nlinalg.py
+++ b/pytensor/link/numba/dispatch/nlinalg.py
@@ -14,7 +14,6 @@
     Det,
     Eig,
     Eigh,
-    Inv,
     MatrixInverse,
     MatrixPinv,
     QRFull,
@@ -125,18 +124,6 @@ def eigh(x):
     return eigh
 
 
-@numba_funcify.register(Inv)
-def numba_funcify_Inv(op, node, **kwargs):
-    out_dtype = node.outputs[0].type.numpy_dtype
-    inputs_cast = int_to_float_fn(node.inputs, out_dtype)
-
-    @numba_basic.numba_njit(inline="always")
-    def inv(x):
-        return np.linalg.inv(inputs_cast(x)).astype(out_dtype)
-
-    return inv
-
-
 @numba_funcify.register(MatrixInverse)
 def numba_funcify_MatrixInverse(op, node, **kwargs):
     out_dtype = node.outputs[0].type.numpy_dtype
diff --git a/pytensor/tensor/nlinalg.py b/pytensor/tensor/nlinalg.py
index 709507afdd..32fa47d28d 100644
--- a/pytensor/tensor/nlinalg.py
+++ b/pytensor/tensor/nlinalg.py
@@ -78,25 +78,6 @@ def pinv(x, hermitian=False):
     return MatrixPinv(hermitian=hermitian)(x)
 
 
-class Inv(Op):
-    """Computes the inverse of one or more matrices."""
-
-    def make_node(self, x):
-        x = as_tensor_variable(x)
-        return Apply(self, [x], [x.type()])
-
-    def perform(self, node, inputs, outputs):
-        (x,) = inputs
-        (z,) = outputs
-        z[0] = np.linalg.inv(x).astype(x.dtype)
-
-    def infer_shape(self, fgraph, node, shapes):
-        return shapes
-
-
-inv = Inv()
-
-
 class MatrixInverse(Op):
     r"""Computes the inverse of a matrix :math:`A`.
 
@@ -169,7 +150,7 @@ def infer_shape(self, fgraph, node, shapes):
         return shapes
 
 
-matrix_inverse = MatrixInverse()
+inv = matrix_inverse = MatrixInverse()
 
 
 def matrix_dot(*args):