diff --git a/flang/include/flang/Optimizer/Transforms/CUFCommon.h b/flang/include/flang/Optimizer/Transforms/CUFCommon.h
index b88133489df5e..f019d1893bda4 100644
--- a/flang/include/flang/Optimizer/Transforms/CUFCommon.h
+++ b/flang/include/flang/Optimizer/Transforms/CUFCommon.h
@@ -20,6 +20,8 @@ namespace cuf {
 mlir::gpu::GPUModuleOp getOrCreateGPUModule(mlir::ModuleOp mod,
                                             mlir::SymbolTable &symTab);
 
+bool isInCUDADeviceContext(mlir::Operation *op);
+
 } // namespace cuf
 
 #endif // FORTRAN_OPTIMIZER_TRANSFORMS_CUFCOMMON_H_
diff --git a/flang/lib/Optimizer/Transforms/CUFCommon.cpp b/flang/lib/Optimizer/Transforms/CUFCommon.cpp
index 162df8f9cab9c..5b7631bbacb5f 100644
--- a/flang/lib/Optimizer/Transforms/CUFCommon.cpp
+++ b/flang/lib/Optimizer/Transforms/CUFCommon.cpp
@@ -7,6 +7,8 @@
 //===----------------------------------------------------------------------===//
 
 #include "flang/Optimizer/Transforms/CUFCommon.h"
+#include "flang/Optimizer/Dialect/CUF/CUFOps.h"
+#include "mlir/Dialect/Func/IR/FuncOps.h"
 #include "mlir/Dialect/LLVMIR/NVVMDialect.h"
 
 /// Retrieve or create the CUDA Fortran GPU module in the give in \p mod.
@@ -26,3 +28,18 @@ mlir::gpu::GPUModuleOp cuf::getOrCreateGPUModule(mlir::ModuleOp mod,
   symTab.insert(gpuMod, insertPt);
   return gpuMod;
 }
+
+bool cuf::isInCUDADeviceContext(mlir::Operation *op) {
+  if (!op)
+    return false;
+  if (op->getParentOfType<cuf::KernelOp>() ||
+      op->getParentOfType<mlir::gpu::GPUFuncOp>())
+    return true;
+  if (auto funcOp = op->getParentOfType<mlir::func::FuncOp>()) {
+    if (auto cudaProcAttr = funcOp->getAttrOfType<cuf::ProcAttributeAttr>(
+            cuf::getProcAttrName())) {
+      return cudaProcAttr.getValue() != cuf::ProcAttribute::Host;
+    }
+  }
+  return false;
+}
diff --git a/flang/lib/Optimizer/Transforms/SimplifyIntrinsics.cpp b/flang/lib/Optimizer/Transforms/SimplifyIntrinsics.cpp
index c61179a7460e3..d3567f453fceb 100644
--- a/flang/lib/Optimizer/Transforms/SimplifyIntrinsics.cpp
+++ b/flang/lib/Optimizer/Transforms/SimplifyIntrinsics.cpp
@@ -31,6 +31,7 @@
 #include "flang/Optimizer/Dialect/FIRType.h"
 #include "flang/Optimizer/Dialect/Support/FIRContext.h"
 #include "flang/Optimizer/HLFIR/HLFIRDialect.h"
+#include "flang/Optimizer/Transforms/CUFCommon.h"
 #include "flang/Optimizer/Transforms/Passes.h"
 #include "flang/Optimizer/Transforms/Utils.h"
 #include "flang/Runtime/entry-names.h"
@@ -1276,6 +1277,8 @@ void SimplifyIntrinsicsPass::runOnOperation() {
   fir::KindMapping kindMap = fir::getKindMapping(module);
   module.walk([&](mlir::Operation *op) {
     if (auto call = mlir::dyn_cast<fir::CallOp>(op)) {
+      if (cuf::isInCUDADeviceContext(op))
+        return;
       if (mlir::SymbolRefAttr callee = call.getCalleeAttr()) {
         mlir::StringRef funcName = callee.getLeafReference().getValue();
         // Replace call to runtime function for SUM when it has single
diff --git a/flang/test/Fir/CUDA/cuda-device-context.mlir b/flang/test/Fir/CUDA/cuda-device-context.mlir
new file mode 100644
index 0000000000000..89d68721ccaf2
--- /dev/null
+++ b/flang/test/Fir/CUDA/cuda-device-context.mlir
@@ -0,0 +1,49 @@
+// RUN: fir-opt --simplify-intrinsics %s | FileCheck %s
+
+func.func @_QPsum_in_device(%arg0: !fir.ref<!fir.array<?xi32>> {cuf.data_attr = #cuf.cuda<device>, fir.bindc_name = "a"}, %arg1: i32 {fir.bindc_name = "n"}) attributes {cuf.proc_attr = #cuf.cuda_proc<global>} {
+  %c5_i32 = arith.constant 5 : i32
+  %c1 = arith.constant 1 : index
+  %c0 = arith.constant 0 : index
+  %c-1 = arith.constant -1 : index
+  %0 = fir.dummy_scope : !fir.dscope
+  %1 = fir.shape %c-1 : (index) -> !fir.shape<1>
+  %2 = fir.declare %arg0(%1) dummy_scope %0 {data_attr = #cuf.cuda<device>, uniq_name = "_QFsum_in_deviceEa"} : (!fir.ref<!fir.array<?xi32>>, !fir.shape<1>, !fir.dscope) -> !fir.ref<!fir.array<?xi32>>
+  %3 = fir.embox %2(%1) : (!fir.ref<!fir.array<?xi32>>, !fir.shape<1>) -> !fir.box<!fir.array<?xi32>>
+  %4 = fir.alloca i32
+  fir.store %arg1 to %4 : !fir.ref<i32>
+  %5 = fir.declare %4 dummy_scope %0 {fortran_attrs = #fir.var_attrs<value>, uniq_name = "_QFsum_in_deviceEn"} : (!fir.ref<i32>, !fir.dscope) -> !fir.ref<i32>
+  %12 = fir.alloca i32 {bindc_name = "i", uniq_name = "_QFsum_in_deviceEi"}
+  %13 = fir.declare %12 {uniq_name = "_QFsum_in_deviceEi"} : (!fir.ref<i32>) -> !fir.ref<i32>
+  %14 = fir.address_of(@_QM__fortran_builtinsE__builtin_threadidx) : !fir.ref<!fir.type<_QM__fortran_builtinsT__builtin_dim3{x:i32,y:i32,z:i32}>>
+  %18 = fir.load %5 : !fir.ref<i32>
+  %19 = fir.convert %18 : (i32) -> index
+  %20 = arith.cmpi sgt, %19, %c0 : index
+  %21 = arith.select %20, %19, %c0 : index
+  %22 = fir.alloca !fir.array<?xi32>, %21 {bindc_name = "auto", uniq_name = "_QFsum_in_deviceEauto"}
+  %23 = fir.shape %21 : (index) -> !fir.shape<1>
+  %24 = fir.declare %22(%23) {uniq_name = "_QFsum_in_deviceEauto"} : (!fir.ref<!fir.array<?xi32>>, !fir.shape<1>) -> !fir.ref<!fir.array<?xi32>>
+  %25 = fir.embox %24(%23) : (!fir.ref<!fir.array<?xi32>>, !fir.shape<1>) -> !fir.box<!fir.array<?xi32>>
+  %26 = fir.undefined index
+  %27 = fir.slice %c1, %19, %c1 : (index, index, index) -> !fir.slice<1>
+  %28 = fir.embox %24(%23) [%27] : (!fir.ref<!fir.array<?xi32>>, !fir.shape<1>, !fir.slice<1>) -> !fir.box<!fir.array<?xi32>>
+  %29 = fir.absent !fir.box<i1>
+  %30 = fir.address_of(@_QQclX91d13f6e74caa2f03965d7a7c6a8fdd5) : !fir.ref<!fir.char<1,50>>
+  %31 = fir.convert %28 : (!fir.box<!fir.array<?xi32>>) -> !fir.box<none>
+  %32 = fir.convert %30 : (!fir.ref<!fir.char<1,50>>) -> !fir.ref<i8>
+  %33 = fir.convert %c0 : (index) -> i32
+  %34 = fir.convert %29 : (!fir.box<i1>) -> !fir.box<none>
+  %35 = fir.call @_FortranASumInteger4(%31, %32, %c5_i32, %33, %34) fastmath<contract> : (!fir.box<none>, !fir.ref<i8>, i32, i32, !fir.box<none>) -> i32
+  %36 = fir.load %13 : !fir.ref<i32>
+  %37 = fir.convert %36 : (i32) -> i64
+  %38 = fir.array_coor %2(%1) %37 : (!fir.ref<!fir.array<?xi32>>, !fir.shape<1>, i64) -> !fir.ref<i32>
+  fir.store %35 to %38 : !fir.ref<i32>
+  return
+}
+
+// Check that intrinsic simplification is disabled in CUDA Fortran context. The simplified intrinsic is
+// created in the module op but the device func will be migrated into a gpu module op resulting in a
+// missing symbol error. 
+// The simplified intrinsic could also be migrated to the gpu module but the choice has not be made
+// at this point.
+// CHECK-LABEL: func.func @_QPsum_in_device
+// CHECK-NOT: fir.call @_FortranASumInteger4x1_contract_simplified