diff --git a/sgl-kernel/csrc/attention/cutlass_mla_kernel.cu b/sgl-kernel/csrc/attention/cutlass_mla_kernel.cu
index 53219ea86..6fb9e83f3 100644
--- a/sgl-kernel/csrc/attention/cutlass_mla_kernel.cu
+++ b/sgl-kernel/csrc/attention/cutlass_mla_kernel.cu
@@ -151,7 +151,10 @@ typename T::Fmha::Arguments args_from_options(
        page_size},
       {static_cast<ElementOut*>(out.data_ptr()), stride_O, static_cast<ElementAcc*>(nullptr), stride_LSE},
       hw_info,
-      -1,       // split_kv
+      // TODO(trevor-m): Change split_kv back to -1 when
+      // https://github.com/NVIDIA/cutlass/issues/2274 is fixed. Split_kv=1 will
+      // perform worse with larger context length and smaller batch sizes.
+      1,       // split_kv
       nullptr,  // is_var_split_kv
   };
   // TODO(kaixih@nvidia): When split_kv=-1 and is_var_split_kv=false, we compute
diff --git a/sgl-kernel/tests/test_cutlass_mla.py b/sgl-kernel/tests/test_cutlass_mla.py
index a8aab8d15..d6e506490 100644
--- a/sgl-kernel/tests/test_cutlass_mla.py
+++ b/sgl-kernel/tests/test_cutlass_mla.py
@@ -67,7 +67,7 @@ def test_cutlass_mla_decode(
     pack_factor = 128 // block_size
     block_num = ((block_num + pack_factor - 1) // pack_factor) * pack_factor
 
-    q = torch.randn(bs, h_q, d)
+    q = torch.randn(bs, h_q, d) * 100.0
     block_table = torch.randint(0, bs * block_num, (bs, block_num), dtype=torch.int32)
 
     kv_cache = torch.randn(block_table.numel(), block_size, d)