diff --git a/tests/unit/test_nvfp4_primitives.py b/tests/unit/test_nvfp4_primitives.py
index cc2942e2..f4fa4aea 100644
--- a/tests/unit/test_nvfp4_primitives.py
+++ b/tests/unit/test_nvfp4_primitives.py
@@ -93,10 +93,11 @@ def test_nvfp4_primitives():
     print(f"  a_sf (E8M0) dtype = {a_sf_e8m0.dtype}, shape = {a_sf_e8m0.shape}")
 
     # The runner uses E4M3 or E8M0? Check what quantize actually produces
-    from dsv4.ops.quantize import quantize_to_nvfp4
+    from dsv4.ops.quantize import quantize_activation_nvfp4
     x = torch.randn(4, 512, device='cuda', dtype=torch.bfloat16)
-    x_fp4, x_sf = quantize_to_nvfp4(x)
-    print(f"  quantize_to_nvfp4 output: FP4 dtype={x_fp4.dtype}, SF dtype={x_sf.dtype}")
+    global_scale = torch.tensor(448.0, device='cuda', dtype=torch.float32)
+    x_fp4, x_sf = quantize_activation_nvfp4(x, global_scale)
+    print(f"  quantize_activation_nvfp4 output: FP4 dtype={x_fp4.dtype}, SF dtype={x_sf.dtype}")
     if x_sf.dtype == torch.float8_e4m3fn:
         print(f"  ✅ Scale factors are E4M3 — NVFP4 correct")
     elif x_sf.dtype == torch.float8_e8m0fnu: