diff --git a/src/target/llvm/codegen_llvm.cc b/src/target/llvm/codegen_llvm.cc
index 131c8212c597..8882eb523dcd 100644
--- a/src/target/llvm/codegen_llvm.cc
+++ b/src/target/llvm/codegen_llvm.cc
@@ -928,7 +928,7 @@ llvm::Value* CodeGenLLVM::CreateCast(DataType from, DataType to, llvm::Value* va
   } else if (to.is_bool()) {
     if (from.is_float()) {
       llvm::Constant* zero = llvm::ConstantFP::get(DTypeToLLVMType(from), 0.);
-      return builder_->CreateFCmpONE(value, zero);
+      return builder_->CreateFCmpUNE(value, zero);
     } else {
       llvm::Constant* zero = llvm::ConstantInt::get(DTypeToLLVMType(from), 0);
       return builder_->CreateICmpNE(value, zero);
diff --git a/tests/python/codegen/test_target_codegen_llvm.py b/tests/python/codegen/test_target_codegen_llvm.py
index 88b791d1aa52..e23ed06211d9 100644
--- a/tests/python/codegen/test_target_codegen_llvm.py
+++ b/tests/python/codegen/test_target_codegen_llvm.py
@@ -378,6 +378,31 @@ def check_llvm(n):
     check_llvm(64)
 
 
+@tvm.testing.requires_llvm
+def test_llvm_cast_float_to_bool():
+    a_np = np.array([0.0, 1.0, np.nan, np.inf], dtype="float32")
+    n = a_np.shape[0]
+
+    A = te.placeholder((n,), name="A", dtype="float32")
+    C = te.compute((n,), lambda i: A[i].astype("bool"), name="C")
+
+    # Convert to TIR and create schedule
+    mod = te.create_prim_func([A, C])
+    sch = tir.Schedule(mod)
+
+    # build and invoke the kernel.
+    f = tvm.compile(sch.mod, target="llvm")
+    dev = tvm.cpu(0)
+
+    # launch the kernel.
+    a = tvm.runtime.tensor(a_np, dev)
+    c = tvm.runtime.empty((n,), dtype="bool", device=dev)
+    f(a, c)
+    c_np = np.array([False, True, True, True], dtype="bool")
+
+    tvm.testing.assert_allclose(c.numpy(), c_np)
+
+
 @tvm.testing.requires_llvm
 def test_rank_zero():
     def check_llvm(n):