diff --git a/lib/Dialect/TritonGPU/Transforms/OptimizeAccumulatorInit.cpp b/lib/Dialect/TritonGPU/Transforms/OptimizeAccumulatorInit.cpp
index dd9b4ad139f5..2111d6241c6a 100644
--- a/lib/Dialect/TritonGPU/Transforms/OptimizeAccumulatorInit.cpp
+++ b/lib/Dialect/TritonGPU/Transforms/OptimizeAccumulatorInit.cpp
@@ -65,6 +65,8 @@ std::optional<std::pair<Operation *, int>> findZeroInitOp(Value accUse,
     return std::nullopt;
   }
   if (auto selOp = dyn_cast<arith::SelectOp>(defOp)) {
+    if (!selOp.getCondition().getType().isInteger(1))
+      return std::nullopt;
     if (isConstantZeroTensor(selOp.getTrueValue()) ||
         isConstantZeroTensor(selOp.getFalseValue())) {
       return std::make_pair(selOp, 0);
diff --git a/test/TritonGPU/accumulator-init.mlir b/test/TritonGPU/accumulator-init.mlir
index 72ef11dcafd7..2f56d0e97511 100644
--- a/test/TritonGPU/accumulator-init.mlir
+++ b/test/TritonGPU/accumulator-init.mlir
@@ -348,4 +348,20 @@ module attributes {"triton_gpu.num-ctas" = 1 : i32, "triton_gpu.num-warps" = 4 :
     }
     tt.return %17 : tensor<128x16xf32, #mma1>
   }
+
+// If the condition is a tensor skip the optimization.
+// CHECK-LABEL: @negative_sel_tensor
+// CHECK-NOT: %[[ACC_NEXT:.+]] = triton_nvidia_gpu.warp_group_dot {{.*}}, {{.*}}, {{.*}}, {{.*}} : !tt.memdesc
+  tt.func @negative_sel_tensor(%A: !tt.memdesc<128x64xf16, #shared, #triton_gpu.shared_memory>, %B: !tt.memdesc<64x16xf16, #shared1, #triton_gpu.shared_memory>, %cnd: tensor<128x16xi1, #mma1>) -> tensor<128x16xf32, #mma1> {
+    %c0_i32 = arith.constant 0 : i32
+    %cst_2 = arith.constant dense<0.000000e+00> : tensor<128x16xf32, #mma1>
+    %c1_i32 = arith.constant 1 : i32
+    %c8_i32 = arith.constant 8 : i32
+    %17 = scf.for %arg3 = %c0_i32 to %c8_i32 step %c1_i32 iter_args(%arg4 = %cst_2) -> (tensor<128x16xf32, #mma1>)  : i32 {
+      %acc_ = arith.select %cnd, %cst_2, %arg4 : tensor<128x16xi1, #mma1>, tensor<128x16xf32, #mma1>
+      %acc = triton_nvidia_gpu.warp_group_dot %A, %B, %acc_ : !tt.memdesc<128x64xf16, #shared, #triton_gpu.shared_memory> * !tt.memdesc<64x16xf16, #shared1, #triton_gpu.shared_memory> -> tensor<128x16xf32, #mma1>
+      scf.yield %acc: tensor<128x16xf32, #mma1>
+    }
+    tt.return %17 : tensor<128x16xf32, #mma1>
+  }
 }