diff --git a/tests/unit/test_kv_quantize.py b/tests/unit/test_kv_quantize.py
index b198d396..443b0304 100644
--- a/tests/unit/test_kv_quantize.py
+++ b/tests/unit/test_kv_quantize.py
@@ -64,13 +64,13 @@ for M in [1, 4, 32, 128]:
 # ===========================================================================
 print("\n--- Test 3: FP32 RoPE (production rope_dim=64, hd=512) ---")
 hd = 512; rope_dim = 64
-cos_cache = torch.randn(1024, rope_dim // 2, device=device, dtype=torch.float32)
-sin_cache = torch.randn(1024, rope_dim // 2, device=device, dtype=torch.float32)
-# Normalize for proper RoPE
-for i in range(1024):
-    norm = (cos_cache[i] ** 2 + sin_cache[i] ** 2).sqrt().clamp(min=1e-8)
-    cos_cache[i] /= norm
-    sin_cache[i] /= norm
+# Build proper RoPE cache (same as single_shot build_rope_cache)
+theta = 10000.0
+freqs = 1.0 / (theta ** (torch.arange(0, rope_dim, 2, dtype=torch.float32) / rope_dim))
+angles = torch.outer(torch.arange(1024, dtype=torch.float32), freqs)
+cos_cache = torch.cos(angles).to(device)  # (1024, rope_dim/2) FP32
+sin_cache = torch.sin(angles).to(device)  # (1024, rope_dim/2) FP32
+# cos²+sin²=1 by construction
 
 for M in [1, 4, 8]:
     data = torch.randn(M, hd, device=device, dtype=torch.float32) * 2.0