diff --git a/test/opt/test_hand_coded_opts.py b/test/opt/test_hand_coded_opts.py
deleted file mode 100644
index 8c9e2e2f01..0000000000
--- a/test/opt/test_hand_coded_opts.py
+++ /dev/null
@@ -1,60 +0,0 @@
-import unittest
-from tinygrad import Tensor, Device
-from tinygrad.helpers import prod
-from tinygrad.uop.ops import AxisType
-from tinygrad.codegen.opt.heuristic import hand_coded_optimizations
-
-# TODO: remove this
-from tinygrad.codegen.opt.kernel import Kernel
-from test.test_linearizer import push_views, helper_linearizer_opt
-
-class TestHandCodedOpts(unittest.TestCase):
-  def test_masked_upcast(self):
-    layer_1 = Tensor.cat(*[Tensor.empty(5) for _ in range(4)])
-    layer_2 = Tensor.cat(layer_1.unsqueeze(0), Tensor.empty(6, 20))
-
-    s = layer_2.schedule()[-1]
-    k = Kernel(push_views(s.ast))
-    k.apply_opts(hand_coded_optimizations(k))
-    assert len(k.bufs) == 6  # make sure all ops are done in one kernel
-    # masked upcast should upcast masked axis of size 7
-    # masked upcast should not upcast large (20) last axis
-    # float4/other hcopt shouldn't upcast last axis, since we already have 7 upcast, and the last axis is not very contiguous
-    assert k.upcasted == 1 and k.full_shape[-1] == 7
-
-  @unittest.skipIf(Device.DEFAULT in {"METAL", "WEBGPU"}, "METAL/WEBGPU split this kernel since it has 37 buffers")
-  def test_masked_upcast_wino(self):
-    monster = Tensor.stack(*[Tensor.stack(*[Tensor.empty(16) for _ in range(6)]) for _ in range(6)])
-
-    s = monster.schedule()[-1]
-    k = Kernel(push_views(s.ast))
-    k.apply_opts(hand_coded_optimizations(k))
-    assert len(k.bufs) == 37  # make sure all ops are done in one kernel
-    # should upcast the two Tensor.stacks
-    assert k.upcasted >= 2 and k.full_shape[k.shape_len-k.upcasted:k.shape_len].count(6) == 2
-
-  def test_masked_upcast_many(self):
-    layer_1 = Tensor.cat(Tensor.rand(3, 4), Tensor.rand(4, 4))
-    layer_2 = Tensor.cat(layer_1.unsqueeze(0), Tensor.rand(6, 7, 4))
-    layer_3 = Tensor.cat(layer_2.unsqueeze(0), Tensor.rand(6, 7, 7, 4))
-
-    k = helper_linearizer_opt(layer_3)[-1]
-    assert len(k.bufs) == 5  # make sure all ops are done in one kernel
-    # check that we don't do too many upcasts
-    assert prod(k.full_shape[k.shape_len-k.upcasted:k.shape_len]) <= 49
-
-  @unittest.skipUnless(Device[Device.DEFAULT].renderer.has_local, "test requires locals")
-  def test_matvec(self):
-    N = 128
-    a = Tensor.rand(1, N).realize()
-    b = Tensor.rand(N, N).realize()
-    c = a @ b
-
-    k = helper_linearizer_opt(c)[-1]
-
-    assert k.group_for_reduces == 1
-    assert k.axis_types.count(AxisType.LOCAL) == 1
-    assert k.upcasted == 1
-
-if __name__ == '__main__':
-  unittest.main()
diff --git a/test/test_linearizer.py b/test/test_linearizer.py
index e3076e5235..53c18aec0e 100644
--- a/test/test_linearizer.py
+++ b/test/test_linearizer.py
@@ -16,7 +16,7 @@ from tinygrad.dtype import DType, dtypes, PtrDType, AddrSpace
 from tinygrad.codegen import apply_rewrites, rewrites_for_views
 
 # TODO: remove this
-from tinygrad.codegen.opt.kernel import Kernel
+#from tinygrad.codegen.opt.kernel import Kernel
 
 class TestLinearizer(unittest.TestCase):
   def test_arg_dedup(self):