diff --git a/tinygrad/codegen/kernel.py b/tinygrad/codegen/kernel.py
index ebdd06162c..b1c96c8beb 100644
--- a/tinygrad/codegen/kernel.py
+++ b/tinygrad/codegen/kernel.py
@@ -111,6 +111,9 @@ class Kernel:
   @property
   def upcast_in_mid_reduce_axes(self) -> List[int]: return [j for j in range(self.first_reduce, self.first_reduce+len(self.group_for_reduce)) if self.full_shape[j] == self.sts[0].shape[j]]
 
+  @property
+  def global_dims(self) -> int: return self.first_reduce-self.local_dims
+
   # there's seven chunks of the shape
   # blue   -- global dims
   # cyan   -- local dims
@@ -123,9 +126,9 @@ class Kernel:
   # yellow -- normal upcasted dimensions
   def colors(self) -> List[str]:
     # up to first_reduce, they are all global (blue)
-    colors = ["blue"] * (self.first_reduce-self.local_dims)
+    colors = ["blue"] * self.global_dims
     # except the local_dims, these are non-reduce locals (cyan)
-    colors += ["cyan"] * (self.local_dims)
+    colors += ["cyan"] * self.local_dims
     # between first_reduce and first_reduce + group_for_reduce, they are either local (cyan), or late upcasted (green)
     colors += ["white" if i in self.upcast_in_mid_reduce_axes else "green" for i in range(self.first_reduce, self.first_reduce + len(self.group_for_reduce))]
     # between first_reduce + group_for_reduce and upcasted, they are reduce (red)
diff --git a/tinygrad/codegen/linearizer.py b/tinygrad/codegen/linearizer.py
index b791a0238b..7c22680f86 100644
--- a/tinygrad/codegen/linearizer.py
+++ b/tinygrad/codegen/linearizer.py
@@ -200,7 +200,8 @@ class Linearizer(OptimizedKernel):
     self.process()
 
     # limit dims if we need to
-    if self.opts.global_max and self.opts.local_max: self.limit_global_dims(3, self.opts.global_max, self.opts.local_max)
+    self.limit_global_dim_count(3)
+    if self.opts.global_max and self.opts.local_max: self.limit_dims_to_max(self.opts.global_max, self.opts.local_max)
 
     # uops
     self.uops: List[UOp] = []
diff --git a/tinygrad/codegen/optimizer.py b/tinygrad/codegen/optimizer.py
index 70182c3a10..ff6584627d 100644
--- a/tinygrad/codegen/optimizer.py
+++ b/tinygrad/codegen/optimizer.py
@@ -92,14 +92,16 @@ class OptimizedKernel(Kernel):
           new_shape[next_idx] = new_shape[next_idx] * 2
     return tuple(new_shape)
 
-  def limit_global_dims(self, limit: int, global_max: List[int], local_max: List[int]):
+  def limit_global_dim_count(self, limit:int):
     # sometimes, there's more dimensions than len(self.lang.gid).
     # compact all the dimensions into the first
     # NOTE: this might make multiview shapetrackers
-    if (self.first_reduce-self.local_dims) > limit:
-      num_to_merge = ((self.first_reduce-self.local_dims) - limit)+1
+    if self.global_dims > limit:
+      num_to_merge = (self.global_dims - limit)+1
       self.reshape_and_permute(lambda x: (prod(x[0:num_to_merge]),)+x[num_to_merge:], None)
       if DEBUG >= 3: print("reshaped to", self.full_shape, "due to too many global dimensions")
+
+  def limit_dims_to_max(self, global_max: List[int], local_max: List[int]):
     # Check the global allocation limit, current the global_size will be flipped during codegen
     # and then padded right with 1s if its length < 3 which makes this part a bit awkward to write
     global_dims = self.first_reduce-self.local_dims