diff --git a/.github/workflows/regression_test.yml b/.github/workflows/regression_test.yml
index 076041d193..2726ced40a 100644
--- a/.github/workflows/regression_test.yml
+++ b/.github/workflows/regression_test.yml
@@ -23,11 +23,6 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - name: CUDA 2.2.2
-            runs-on: linux.g5.12xlarge.nvidia.gpu
-            torch-spec: 'torch==2.2.2 "numpy<2" '
-            gpu-arch-type: "cuda"
-            gpu-arch-version: "12.1"
           - name: CUDA 2.3
             runs-on: linux.g5.12xlarge.nvidia.gpu
             torch-spec: 'torch==2.3.0'
@@ -38,17 +33,17 @@ jobs:
             torch-spec: 'torch==2.4.0'
             gpu-arch-type: "cuda"
             gpu-arch-version: "12.1"
+          - name: CUDA 2.5
+            runs-on: linux.g5.12xlarge.nvidia.gpu
+            torch-spec: 'torch==2.5.0 --index-url https://download.pytorch.org/whl/cu121'
+            gpu-arch-type: "cuda"
+            gpu-arch-version: "12.1"
           - name: CUDA Nightly
             runs-on: linux.g5.12xlarge.nvidia.gpu
             torch-spec: '--pre torch --index-url https://download.pytorch.org/whl/nightly/cu121'
             gpu-arch-type: "cuda"
             gpu-arch-version: "12.1"
 
-          - name: CPU 2.2.2
-            runs-on: linux.4xlarge
-            torch-spec: 'torch==2.2.2 --index-url https://download.pytorch.org/whl/cpu "numpy<2" '
-            gpu-arch-type: "cpu"
-            gpu-arch-version: ""
           - name: CPU 2.3
             runs-on: linux.4xlarge
             torch-spec: 'torch==2.3.0 --index-url https://download.pytorch.org/whl/cpu'
@@ -59,6 +54,11 @@ jobs:
             torch-spec: 'torch==2.4.0 --index-url https://download.pytorch.org/whl/cpu'
             gpu-arch-type: "cpu"
             gpu-arch-version: ""
+          - name: CPU 2.5
+            runs-on: linux.4xlarge
+            torch-spec: 'torch==2.5.0 --index-url https://download.pytorch.org/whl/cpu'
+            gpu-arch-type: "cpu"
+            gpu-arch-version: ""
           - name: CPU Nightly
             runs-on: linux.4xlarge
             torch-spec: '--pre torch --index-url https://download.pytorch.org/whl/nightly/cpu'
diff --git a/test/dtypes/test_affine_quantized_tensor_parallel.py b/test/dtypes/test_affine_quantized_tensor_parallel.py
index 42511e7db8..af07328407 100644
--- a/test/dtypes/test_affine_quantized_tensor_parallel.py
+++ b/test/dtypes/test_affine_quantized_tensor_parallel.py
@@ -18,7 +18,7 @@
 )
 from torchao.quantization.quant_api import quantize_
 from torchao.dtypes import AffineQuantizedTensor
-from torchao.utils import TORCH_VERSION_AT_LEAST_2_5
+from torchao.utils import TORCH_VERSION_AT_LEAST_2_6
 
 class TestAffineQuantizedTensorParallel(DTensorTestBase):
     """Basic test case for tensor subclasses
@@ -111,8 +111,8 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
 
         y_d = dn_dist(up_dist(input_dtensor))
 
-        if not TORCH_VERSION_AT_LEAST_2_5:
-            # Need torch 2.5 to support compiled tensor parallelism
+        if not TORCH_VERSION_AT_LEAST_2_6:
+            # Need torch 2.6 to support compiled tensor parallelism
             return
 
         up_compiled = torch.compile(up_dist)
diff --git a/torchao/testing/utils.py b/torchao/testing/utils.py
index 5211065e14..39edc50085 100644
--- a/torchao/testing/utils.py
+++ b/torchao/testing/utils.py
@@ -10,7 +10,7 @@
 from torchao.dtypes import to_affine_quantized_intx
 from torchao.quantization.quant_primitives import MappingType
 from torchao.quantization import quantize_, int8_weight_only
-from torchao.utils import TORCH_VERSION_AT_LEAST_2_5
+from torchao.utils import TORCH_VERSION_AT_LEAST_2_6
 
 """
 How to use:
@@ -322,8 +322,8 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
 
         y_d = dn_dist(up_dist(input_dtensor))
 
-        if not TORCH_VERSION_AT_LEAST_2_5:
-            # Need torch 2.5 to support compiled tensor parallelism
+        if not TORCH_VERSION_AT_LEAST_2_6:
+            # Need torch 2.6 to support compiled tensor parallelism
             return
 
         up_compiled = torch.compile(up_dist)