diff --git a/test/test_transformers.py b/test/test_transformers.py
index 8dd54ae00dd2..e7ed97eefdc4 100644
--- a/test/test_transformers.py
+++ b/test/test_transformers.py
@@ -66,7 +66,7 @@ def use_deterministic_algorithims(mode: bool, warn_only: bool):
 default_atol = {torch.float16: 1e-3, torch.bfloat16: 1e-3, torch.float32: 1e-5}
 default_rtol = {torch.float16: 1e-3, torch.bfloat16: 1.6e-2, torch.float32: 1.3e-6}
 
-isSM86or89Device = torch.cuda.is_available() and torch.cuda.get_device_capability() in [(8, 6), (8, 9)]
+isSM8XDevice = torch.cuda.is_available() and torch.cuda.get_device_capability() in [(8, 6), (8, 7), (8, 9)]
 isSM90Device = torch.cuda.is_available() and torch.cuda.get_device_capability() == (9, 0)
 isSM5xDevice = torch.cuda.is_available() and torch.cuda.get_device_capability()[0] == 5
 isLessThanSM80Device = torch.cuda.is_available() and torch.cuda.get_device_capability()[0] < 8
@@ -1322,7 +1322,7 @@ class TestSDPAFailureModes(NNTestCase):
     _do_cuda_non_default_stream = True
 
     @onlyCUDA
-    @unittest.skipIf(not PLATFORM_SUPPORTS_FLASH_ATTENTION or not isSM86or89Device,
+    @unittest.skipIf(not PLATFORM_SUPPORTS_FLASH_ATTENTION or not isSM8XDevice,
                      "Does not support fused SDPA or not SM86+ hardware")
     @parametrize("head_dim", [193, 204, 256])
     def test_flash_backward_failure_sm86plus(self, device, head_dim: int):
@@ -2676,8 +2676,8 @@ def is_power_of_2(n):
             if head_dim > 128:
                 self.skipTest("Flash attention on ROCM only supports power of two headdim <= 128, for now.")
 
-        if isSM86or89Device and head_dim in range(193, 256 + 1):
-            self.skipTest("Flash attention on sm86 and sm89 for headdim > 192 currently disabled")
+        if isSM8XDevice and head_dim in range(193, 256 + 1):
+            self.skipTest("Flash attention on sm86, sm87, and sm89 for headdim > 192 currently disabled")
         if is_causal and seq_len_q != seq_len_k:
             self.skipTest("Flash V2 does not accept is_casual when seq_len_q != seq_len_k")
 
@@ -2742,8 +2742,8 @@ def is_power_of_2(n):
 
         upstream_grad = torch.rand_like(out, requires_grad=False)
 
-        # backward for flash attention on sm86 and sm89 for headdim > 64 currently disabled
-        if isSM86or89Device and head_dim in range(193, 256):
+        # backward for flash attention on sm86, sm87, and sm89 for headdim >= 193 currently disabled
+        if isSM8XDevice and head_dim in range(193, 256):
             self.assertRaises(RuntimeError, lambda: out.backward(upstream_grad))
             return
         out.backward(upstream_grad)