diff --git a/python/tutorials/09-persistent-matmul.py b/python/tutorials/09-persistent-matmul.py
index 27448b87a922..d4fc294e11d7 100644
--- a/python/tutorials/09-persistent-matmul.py
+++ b/python/tutorials/09-persistent-matmul.py
@@ -732,21 +732,20 @@ def show_profile(precision, profile_name):
 
     if args.prec == 'fp8' and (not hasattr(torch, "float8_e4m3fn") or not is_cuda()):
         print("This example requires CUDA with fp8 support.")
-        exit(1)
-
-    dtype = torch.float8_e4m3fn if args.prec == 'fp8' else torch.float16
+    else:
+        dtype = torch.float8_e4m3fn if args.prec == 'fp8' else torch.float16
 
-    if args.K and args.K_range is None:
-        args.K_range = [args.K, args.K]
-        args.K_step = 1  # doesn't matter as long as it's not 0
+        if args.K and args.K_range is None:
+            args.K_range = [args.K, args.K]
+            args.K_step = 1  # doesn't matter as long as it's not 0
 
-    torch.manual_seed(0)
+        torch.manual_seed(0)
 
-    validate(32, 32, 32, dtype)
-    validate(8192, 8192, args.K_range[0], dtype)
+        validate(32, 32, 32, dtype)
+        validate(8192, 8192, args.K_range[0], dtype)
 
-    proton.start("matmul", hook="triton")
-    for K in range(args.K_range[0], args.K_range[1] + 1, args.K_step):
-        bench(K, dtype)
-    proton.finalize()
-    show_profile(args.prec, "matmul")
+        proton.start("matmul", hook="triton")
+        for K in range(args.K_range[0], args.K_range[1] + 1, args.K_step):
+            bench(K, dtype)
+        proton.finalize()
+        show_profile(args.prec, "matmul")
diff --git a/python/tutorials/10-block-scaled-matmul.py b/python/tutorials/10-block-scaled-matmul.py
index e664fe39db2a..a97d1118b50c 100644
--- a/python/tutorials/10-block-scaled-matmul.py
+++ b/python/tutorials/10-block-scaled-matmul.py
@@ -324,17 +324,16 @@ def show_profile(profile_name):
     parser.add_argument("--format", type=str, choices=["mxfp4", "nvfp4", "mxfp8"], default="nvfp4")
     args = parser.parse_args()
 
-    torch.manual_seed(42)
-
     if not supports_block_scaling():
         print("⛔ This example requires GPU support for block scaled matmul")
-        exit(1)
+    else:
+        torch.manual_seed(42)
 
-    validate_block_scaled(8192, 8192, 8192, block_scale_type=args.format)
+        validate_block_scaled(8192, 8192, 8192, block_scale_type=args.format)
 
-    if args.bench:
-        proton.start("block_scaled_matmul", hook="triton")
-        for K in range(args.K_range[0], args.K_range[1] + 1, args.K_step):
-            bench_block_scaled(K, reps=10000, block_scale_type=args.format)
-        proton.finalize()
-        show_profile("block_scaled_matmul")
+        if args.bench:
+            proton.start("block_scaled_matmul", hook="triton")
+            for K in range(args.K_range[0], args.K_range[1] + 1, args.K_step):
+                bench_block_scaled(K, reps=10000, block_scale_type=args.format)
+            proton.finalize()
+            show_profile("block_scaled_matmul")