diff --git a/facto/inputgen/argtuple/gen.py b/facto/inputgen/argtuple/gen.py
index cb6e6f4..390b3ca 100644
--- a/facto/inputgen/argtuple/gen.py
+++ b/facto/inputgen/argtuple/gen.py
@@ -16,6 +16,27 @@
 from facto.inputgen.utils.config import Condition, TensorConfig
 
 
+def compare_tensors(x, y):
+    x = x.to(torch.float)
+    y = y.to(torch.float)
+    c = torch.isclose(x, y, atol=1e-4, rtol=1e-2, equal_nan=True)
+    if c.all():
+        return True, 0, lambda t: t
+    else:
+        d = x[c == False] - y[c == False]
+        x_d = x[c == False]
+        y_d = y[c == False]
+        xy = torch.logical_or(
+            torch.logical_and(x_d > 1e30, y_d == float("inf")),
+            torch.logical_and(x_d == float("inf"), y_d > 1e30),
+        )
+        if xy.all():
+            return True, 0, lambda t: t
+        else:
+            ix = xy == False
+            return False, d[ix].abs().max().item(), lambda t: t[c == False][ix]
+
+
 class ArgumentTupleGenerator:
     def __init__(self, spec: Spec, config: Optional[TensorConfig] = None):
         self.spec = spec
@@ -188,21 +209,23 @@ def gen_errors(
                         if isinstance(ret, torch.Tensor) and isinstance(
                             cpu_ret, torch.Tensor
                         ):
-                            if not torch.allclose(
-                                cpu_ret, ret.to("cpu"), equal_nan=True
-                            ):
-                                cpu_ret_f = cpu_ret.to(torch.float)
-                                ret_f = ret.to("cpu").to(torch.float)
-
-                                max_diff = (cpu_ret_f - ret_f).abs().max()
+                            allclose, max_diff, ix_fun = compare_tensors(
+                                cpu_ret, ret.to("cpu")
+                            )
+                            if not allclose:
                                 if verbose:
                                     print(f"Output mismatch: {max_diff}")
                                     print(
                                         op.__name__, str([str(x) for x in meta_tuple])
                                     )
-                                    if ret.numel() < 10:
-                                        print(ret)
-                                        print(cpu_ret)
+                                    # for cpu_arg in cpu_posargs:
+                                    #     if isinstance(cpu_arg, torch.Tensor) and cpu_arg.numel() < 10:
+                                    #         print(cpu_arg)
+                                    #     elif isinstance(cpu_arg, torch.Tensor) and cpu_arg.shape == cpu_ret.shape:
+                                    #         print(ix_fun(cpu_arg))
+                                    # if ret.numel() < 10:
+                                    #     print(ret)
+                                    #     print(cpu_ret)
                                 yield posargs, inkwargs, outargs
                 else:
                     # When valid=False, we expect failure, so success IS a bug