diff --git a/lib/Conversion/TorchToStablehlo/Basic.cpp b/lib/Conversion/TorchToStablehlo/Basic.cpp
index 1f21a1afe..ab4e284f8 100644
--- a/lib/Conversion/TorchToStablehlo/Basic.cpp
+++ b/lib/Conversion/TorchToStablehlo/Basic.cpp
@@ -516,13 +516,12 @@ public:
     if (!lhsTy) {
       return op.emitError("only Tensor types supported in StableHLO");
     }
+    bool isRhsScalar = false;
     if (!rhsTy) {
       rhs = hlo::scalarToStablehloTensor(rewriter, op, adaptor.getOther(),
                                          rhs.getType());
-      // use lhs's element type as compute type
-      rhs =
-          hlo::promoteType(rewriter, op.getLoc(), rhs, lhsTy.getElementType());
       rhsTy = dyn_cast<RankedTensorType>(rhs.getType());
+      isRhsScalar = true;
     }
 
     auto outType = cast<RankedTensorType>(
@@ -537,16 +536,28 @@ public:
     }
 
     if (isa<mlir::IntegerType>(lhsElemTy) && isa<mlir::FloatType>(rhsElemTy)) {
-      lhs = hlo::promoteType(rewriter, op.getLoc(), lhs, rhsElemTy);
+      // torch.lt(x_int, 1.1) use fp32 as compute type
+      // torch.lt(x_int, y_float) use y's float type as compute type
+      Type promoteTo = isRhsScalar ? rewriter.getF32Type() : rhsElemTy;
+      lhs = hlo::promoteType(rewriter, op.getLoc(), lhs, promoteTo);
+      rhs = hlo::promoteType(rewriter, op.getLoc(), rhs, promoteTo);
     } else if (isa<mlir::FloatType>(lhsElemTy) &&
                isa<mlir::IntegerType>(rhsElemTy)) {
+      // always use lhs's float type as compute type
       rhs = hlo::promoteType(rewriter, op.getLoc(), rhs, lhsElemTy);
     } else {
-      if (lhsElemTy.getIntOrFloatBitWidth() >
-          rhsElemTy.getIntOrFloatBitWidth()) {
+      if (isRhsScalar) {
+        // torch.lt(x_float, 1.1) use x's float type as compute type
+        // torch.lt(x_int, 1) use x's int type as compute type
         rhs = hlo::promoteType(rewriter, op.getLoc(), rhs, lhsElemTy);
       } else {
-        lhs = hlo::promoteType(rewriter, op.getLoc(), lhs, rhsElemTy);
+        // torch.lt(x_float, y_float) use higher bitwidth as compute type
+        Type promoteTo = lhsElemTy.getIntOrFloatBitWidth() >
+                                 rhsElemTy.getIntOrFloatBitWidth()
+                             ? lhsElemTy
+                             : rhsElemTy;
+        lhs = hlo::promoteType(rewriter, op.getLoc(), lhs, promoteTo);
+        rhs = hlo::promoteType(rewriter, op.getLoc(), rhs, promoteTo);
       }
     }
     lhsElemTy = dyn_cast<RankedTensorType>(lhs.getType()).getElementType();
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index 918cbae63..c99ef4d96 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -528,7 +528,6 @@ FX_IMPORTER_STABLEHLO_XFAIL_SET = {
     "AtenPolarFloatModule_basic",
     "DiagonalWithStaticShapeModule_basic",
     "EinsumStaticDiagonalDimensionModule_basic",
-    "ElementwiseIntTensorLtFloatScalarModule_basic",
     "ElementwiseRemainderScalarModule_Bool_NegativeDivisor_basic",
     "ElementwiseRemainderScalarModule_Float_NegativeDividend_basic",
     "ElementwiseRemainderScalarModule_Float_NegativeDivisor_basic",