diff --git a/test/test_ops.py b/test/test_ops.py
index 64daff191e..d7e9e0fab9 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -240,7 +240,11 @@ class TestOps(unittest.TestCase):
     helper_test_op([], lambda: torch.linspace(5, 10, 30), lambda: Tensor.linspace(5, 10, 30), forward_only=True)
     helper_test_op([], lambda: torch.linspace(-5.5, 5.5, 10), lambda: Tensor.linspace(-5.5, 5.5, 10), forward_only=True)
     helper_test_op([], lambda: torch.linspace(5.5, -5.5, 10), lambda: Tensor.linspace(5.5, -5.5, 10), forward_only=True)
-    helper_test_op([], lambda: torch.linspace(5, 10, 3, dtype=torch.int32), lambda: Tensor.linspace(5, 10, 3, dtype=dtypes.int32), forward_only=True)
+    helper_test_op([], lambda: torch.linspace(5, 10, 3, dtype=torch.int32), lambda: Tensor.linspace(5, 10, 3, dtype="int32"), forward_only=True)
+    helper_test_op([], lambda: torch.linspace(5, 10, 20, dtype=torch.int32), lambda: Tensor.linspace(5, 10, 20, dtype="int32"), forward_only=True)
+    helper_test_op([], lambda: torch.linspace(5, -5, 20, dtype=torch.int32), lambda: Tensor.linspace(5, -5, 20, dtype="int32"), forward_only=True)
+    self.helper_test_exception([], lambda: torch.linspace(5, 10, 3, dtype=torch.bool), lambda: Tensor.linspace(5, 10, 3, dtype="bool"),
+                               expected=(RuntimeError, ValueError))
     self.helper_test_exception([], lambda: torch.linspace(1, 2, -1), lambda: Tensor.linspace(1, 2, -1), expected=(RuntimeError, ValueError))
 
   def test_sum_fake(self):
diff --git a/test/test_randomness.py b/test/test_randomness.py
index 4258b45b30..4670731174 100644
--- a/test/test_randomness.py
+++ b/test/test_randomness.py
@@ -227,11 +227,15 @@ class TestRandomness(unittest.TestCase):
 
   def test_randint(self):
     self.assertFalse(normal_test(Tensor.randint))
-    self.assertTrue(equal_distribution(partial(Tensor.randint, low=-2, high=5), numpy_func=lambda x: np.random.randint(low=-2, high=5, size=x)))
+    self.assertTrue(equal_distribution(partial(Tensor.randint, low=-2, high=5),
+                                       numpy_func=lambda x: np.random.randint(low=-2, high=5, size=x)))
+    self.assertTrue(equal_distribution(partial(Tensor.randint, low=-2, high=5, dtype="int32"),
+                                       numpy_func=lambda x: np.random.randint(low=-2, high=5, size=x)))
     self.assertTrue(Tensor.randint(1, device="CLANG").device=="CLANG")
     # check types of args
     with self.assertRaises(TypeError): Tensor.randint((3, 4), low=0.1, high=3)
     with self.assertRaises(TypeError): Tensor.randint((3, 4), low=0, high=3.5)
+    with self.assertRaises(TypeError): Tensor.randint((3, 4), low=1, high=3, dtype="float")
     with self.assertRaises(TypeError): Tensor.randint((3, 4), low=0, high=3, dtype=dtypes.float32)
 
   def test_normal(self):
diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index 15df5e5bfe..7d3824d44a 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -628,7 +628,7 @@ class Tensor(SimpleMathTrait):  # pylint: disable=abstract-method
     ```
     """
     if steps < 0: raise ValueError("number of steps must be non-negative")
-    dtype = kwargs.pop("dtype", dtypes.default_float)
+    if (dtype := to_dtype(kwargs.pop("dtype", dtypes.default_float))) == dtypes.bool: raise ValueError("linspace with bool dtype is not supported")
     if steps == 1: return Tensor([start], dtype=dtype, **kwargs)
     return (start + Tensor.arange(steps, **kwargs) * ((stop - start) / (steps - 1))).cast(dtype)
 
@@ -754,7 +754,7 @@ class Tensor(SimpleMathTrait):  # pylint: disable=abstract-method
     ```
     """
     if not isinstance(low, int) or not isinstance(high, int): raise TypeError(f"{low=} and {high=} must be integers")
-    dtype = kwargs.pop("dtype", dtypes.int32)
+    dtype = to_dtype(kwargs.pop("dtype", dtypes.int32))
     if not dtypes.is_int(dtype): raise TypeError(f"{dtype=} must be int")
     return Tensor.uniform(*shape, low=low, high=high, dtype=dtype, **kwargs)