diff --git a/test/test_ops.py b/test/test_ops.py
index 50ac037eb4..928e533eb2 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -23,13 +23,13 @@ def helper_test_op(shps, torch_fxn, tinygrad_fxn=None, atol=1e-6, rtol=1e-3, gra
   ret = tinygrad_fxn(*tst).realize()
   tinygrad_fp = time.monotonic() - st
 
-  def compare(s, x,y,atol,rtol):
-    if PRINT_TENSORS: print(s, x, y)
-    assert x.shape == y.shape, f"shape mismatch: tinygrad={x.shape} | torch={y.shape}"
+  def compare(s, tinygrad_output, torch_output, atol, rtol):
+    if PRINT_TENSORS: print(s, tinygrad_output, torch_output)
+    assert tinygrad_output.shape == torch_output.shape, f"shape mismatch: tinygrad={tinygrad_output.shape} | torch={torch_output.shape}"
     try:
-      np.testing.assert_allclose(x,y, atol=atol, rtol=rtol)
-    except Exception:
-      raise Exception(f"{s} failed shape {x.shape}")
+      np.testing.assert_allclose(tinygrad_output, torch_output, atol=atol, rtol=rtol)
+    except Exception as e:
+      raise Exception(f"{s} failed shape {tinygrad_output.shape}: {e}")
 
   if DEBUG >= 6:
     np.set_printoptions(linewidth=200, suppress=True)
@@ -707,14 +707,38 @@ class TestOps(unittest.TestCase):
     helper_test_op([(10,10,10)], lambda x: x.log_softmax(1), atol=1e-7, grad_atol=1e-7)
     helper_test_op([(10,10,10)], lambda x: x.log_softmax(2), atol=1e-7, grad_atol=1e-7)
 
+  def test_sinh(self):
+    helper_test_op([(45,65)], lambda x: x.sinh(), atol=1e-6, grad_atol=1e-6)
+    # TODO: backward nan instead of inf
+    helper_test_op([(45,65)], lambda x: x.sinh(), atol=1e-6, grad_atol=1e-6, a=-100, forward_only=True)
+    helper_test_op([(45,65)], lambda x: x.sinh(), atol=1e-6, grad_atol=1e-6, a=100, forward_only=True)
+  def test_cosh(self):
+    helper_test_op([(45,65)], lambda x: x.cosh(), atol=1e-6, grad_atol=1e-6)
+    # TODO: backward nan instead of inf
+    helper_test_op([(45,65)], lambda x: x.cosh(), atol=1e-6, grad_atol=1e-6, a=-100, forward_only=True)
+    helper_test_op([(45,65)], lambda x: x.cosh(), atol=1e-6, grad_atol=1e-6, a=100, forward_only=True)
   def test_tanh(self):
     helper_test_op([(45,65)], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6)
     helper_test_op([(45,65)], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6, a=-100)
-    helper_test_op([()], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6)
+    helper_test_op([(45,65)], lambda x: x.tanh(), atol=1e-6, grad_atol=1e-6, a=100)
   def test_hardtanh(self):
     for val in range(10, 30, 5):
       helper_test_op([(45,65)], lambda x: torch.nn.functional.hardtanh(x, -val, val), lambda x: x.hardtanh(-val, val), atol=1e-6, grad_atol=1e-6)
       helper_test_op([()], lambda x: torch.nn.functional.hardtanh(x, -val, val), lambda x: x.hardtanh(-val, val), atol=1e-6, grad_atol=1e-6)
+  def test_asinh(self):
+    helper_test_op([(45,65)], lambda x: x.asinh(), atol=1e-6, grad_atol=1e-6)
+    # NOTE: this one has larger atol
+    helper_test_op([(45,65)], lambda x: x.asinh(), atol=1e-2, grad_atol=1e-6, a=-100)
+    helper_test_op([(45,65)], lambda x: x.asinh(), atol=1e-6, grad_atol=1e-6, a=100)
+  def test_acosh(self):
+    helper_test_op([(45,65)], lambda x: x.acosh(), atol=1e-6, grad_atol=1e-6)
+    helper_test_op([(45,65)], lambda x: x.acosh(), atol=1e-6, grad_atol=1e-6, a=-100)
+    helper_test_op([(45,65)], lambda x: x.acosh(), atol=1e-6, grad_atol=1e-6, a=100)
+  def test_atanh(self):
+    helper_test_op([(45,65)], lambda x: x.atanh(), atol=1e-6, grad_atol=1e-6)
+    helper_test_op([(45,65)], lambda x: x.atanh(), atol=1e-6, grad_atol=1e-6, a=-100)
+    helper_test_op([(45,65)], lambda x: x.atanh(), atol=1e-6, grad_atol=1e-6, a=100)
+
   def test_topo_sort(self):
     helper_test_op([(45,65)], lambda x: (x+x)*x, atol=1e-6, grad_atol=1e-6)
     helper_test_op([()], lambda x: (x+x)*x, atol=1e-6, grad_atol=1e-6)