diff --git a/falkon/kernels/distance_kernel.py b/falkon/kernels/distance_kernel.py
index 6917041..147cbd2 100644
--- a/falkon/kernels/distance_kernel.py
+++ b/falkon/kernels/distance_kernel.py
@@ -552,9 +552,9 @@ def keops_mmv_impl(self, X1, X2, v, kernel, out, opt, kwargs_m1, kwargs_m2):
             )
         elif self.nu == 2.5:
             formula = (
-                "(IntCst(1) + Sqrt(IntCst(5)) * Norm2(x1 / s - x2 / s) + "
+                "((IntCst(1) + Sqrt(IntCst(5)) * Norm2(x1 / s - x2 / s) + "
                 "(IntInv(3) * IntCst(5)) * SqNorm2(x1 / s - x2 / s)) * "
-                "(Exp(-Sqrt(IntCst(5)) * Norm2(x1 / s - x2 / s)) * v)"
+                "Exp(-Sqrt(IntCst(5)) * Norm2(x1 / s - x2 / s))) * v"
             )
         elif self.nu == float("inf"):
             formula = "Exp(IntInv(-2) * SqDist(x1 / s, x2 / s)) * v"
diff --git a/falkon/tests/conftest.py b/falkon/tests/conftest.py
index 81c1a54..f9d9cec 100644
--- a/falkon/tests/conftest.py
+++ b/falkon/tests/conftest.py
@@ -100,7 +100,7 @@ def fix_mats(*mats, order, device, dtype):
     dtype = make_tuple(dtype, len(mats))
     for i, m in enumerate(mats):
         if isinstance(m, SparseTensor):
-            yield fix_sparse_mat(m, dtype=dtype[i], device=device[i])
+            yield fix_sparse_mat(m, device=device[i], dtype=dtype[i])
         else:
             yield fix_mat(m, order=order[i], device=device[i], dtype=dtype[i])
 
diff --git a/falkon/tests/test_kernels.py b/falkon/tests/test_kernels.py
index a6fae31..8185505 100644
--- a/falkon/tests/test_kernels.py
+++ b/falkon/tests/test_kernels.py
@@ -158,6 +158,9 @@ def autogradcheck_mm(_m1, _m2, *_kernel_params):
         actual_noout, actual, rtol=rtol, atol=atol, msg="MMV with out and without return different stuff"
     )
     expected_mmv = expected_mm @ v
+    print(f"{expected_mmv=}")
+    print(f"{actual=}")
+    print(f"Max Diff: {(expected_mmv - actual).square().max().sqrt()}")
     torch.testing.assert_close(expected_mmv, actual, rtol=rtol, atol=atol, msg="MMV result is incorrect")
 
     # 4. MMV gradients