diff --git a/tests/core/converters/test_lstm_cell.cpp b/tests/core/converters/test_lstm_cell.cpp
index 1b7feb55da..43930aeee7 100755
--- a/tests/core/converters/test_lstm_cell.cpp
+++ b/tests/core/converters/test_lstm_cell.cpp
@@ -4,7 +4,7 @@
 #include "tests/util/util.h"
 #include "core/compiler.h"
 
-TEST(Converters, ATenLSTMCellConvertsCorrectlyWithBias) {
+TEST(Converters, ATenLSTMCellConvertsCorrectlyWithBiasCheckHidden) {
     const auto graph = R"IR(
       graph(%0 : Tensor,
             %1 : Tensor,
@@ -53,7 +53,56 @@ TEST(Converters, ATenLSTMCellConvertsCorrectlyWithBias) {
     ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
 }
 
-TEST(Converters, ATenLSTMCellConvertsCorrectlyWithoutBias) {
+TEST(Converters, ATenLSTMCellConvertsCorrectlyWithBiasCheckCell) {
+    const auto graph = R"IR(
+      graph(%0 : Tensor,
+            %1 : Tensor,
+            %2 : Tensor, 
+            %3 : Tensor,
+            %4 : Tensor,
+            %5 : Tensor,
+            %6 : Tensor):
+        %7 : Tensor[] = prim::ListConstruct(%1, %2)
+        %8 : Tensor, %9 : Tensor = aten::lstm_cell(%0, %7, %3, %4, %5, %6)
+        return (%9))IR";
+
+    auto g = std::make_shared<torch::jit::Graph>();
+    torch::jit::parseIR(graph, &*g);
+
+    auto input = at::randn({50, 10}, {at::kCUDA});
+    auto h0 = at::randn({50, 20}, {at::kCUDA});
+    auto c0 = at::randn({50, 20}, {at::kCUDA});
+    auto w_ih = at::randn({4*20, 10}, {at::kCUDA});
+    auto w_hh = at::randn({4*20, 20}, {at::kCUDA});
+    auto b_ih = at::randn({4*20}, {at::kCUDA});
+    auto b_hh = at::randn({4*20}, {at::kCUDA});
+
+    auto jit_input = at::clone(input);
+    auto jit_h0 = at::clone(h0);
+    auto jit_c0 = at::clone(c0);
+    auto jit_w_ih = at::clone(w_ih);
+    auto jit_w_hh = at::clone(w_hh);
+    auto jit_b_ih = at::clone(b_ih);
+    auto jit_b_hh = at::clone(b_hh);
+
+    auto params = trtorch::core::conversion::get_named_params(g->inputs(), {});
+    auto jit_results = trtorch::tests::util::RunGraph(g, params, {jit_input, jit_h0, jit_c0, jit_w_ih, jit_w_hh, jit_b_ih, jit_b_hh});
+
+    auto trt_input = at::clone(input);
+    auto trt_h0 = at::clone(h0);
+    auto trt_c0 = at::clone(c0);
+    auto trt_w_ih = at::clone(w_ih);
+    auto trt_w_hh = at::clone(w_hh);
+    auto trt_b_ih = at::clone(b_ih);
+    auto trt_b_hh = at::clone(b_hh);
+
+    params = trtorch::core::conversion::get_named_params(g->inputs(), {});
+    auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {trt_input, trt_h0, trt_c0, trt_w_ih, trt_w_hh, trt_b_ih, trt_b_hh});
+
+    ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
+}
+
+TEST(Converters, ATenLSTMCellConvertsCorrectlyWithoutBiasCheckHidden) {
     const auto graph = R"IR(
       graph(%0 : Tensor,
             %1 : Tensor,
@@ -93,5 +142,48 @@ TEST(Converters, ATenLSTMCellConvertsCorrectlyWithoutBias) {
     params = trtorch::core::conversion::get_named_params(g->inputs(), {});
     auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {trt_input, trt_h0, trt_c0, trt_w_ih, trt_w_hh});
 
+    ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
+}
+
+TEST(Converters, ATenLSTMCellConvertsCorrectlyWithoutBiasCheckCell) {
+    const auto graph = R"IR(
+      graph(%0 : Tensor,
+            %1 : Tensor,
+            %2 : Tensor, 
+            %3 : Tensor,
+            %4 : Tensor):
+        %5 : None = prim::Constant()
+        %6 : None = prim::Constant()
+        %7 : Tensor[] = prim::ListConstruct(%1, %2)
+        %8 : Tensor, %9 : Tensor = aten::lstm_cell(%0, %7, %3, %4, %5, %6)
+        return (%9))IR";
+
+    auto g = std::make_shared<torch::jit::Graph>();
+    torch::jit::parseIR(graph, &*g);
+
+    auto input = at::randn({50, 10}, {at::kCUDA});
+    auto h0 = at::randn({50, 20}, {at::kCUDA});
+    auto c0 = at::randn({50, 20}, {at::kCUDA});
+    auto w_ih = at::randn({4*20, 10}, {at::kCUDA});
+    auto w_hh = at::randn({4*20, 20}, {at::kCUDA});
+
+    auto jit_input = at::clone(input);
+    auto jit_h0 = at::clone(h0);
+    auto jit_c0 = at::clone(c0);
+    auto jit_w_ih = at::clone(w_ih);
+    auto jit_w_hh = at::clone(w_hh);
+
+    auto params = trtorch::core::conversion::get_named_params(g->inputs(), {});
+    auto jit_results = trtorch::tests::util::RunGraph(g, params, {jit_input, jit_h0, jit_c0, jit_w_ih, jit_w_hh});
+
+    auto trt_input = at::clone(input);
+    auto trt_h0 = at::clone(h0);
+    auto trt_c0 = at::clone(c0);
+    auto trt_w_ih = at::clone(w_ih);
+    auto trt_w_hh = at::clone(w_hh);
+
+    params = trtorch::core::conversion::get_named_params(g->inputs(), {});
+    auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {trt_input, trt_h0, trt_c0, trt_w_ih, trt_w_hh});
+
     ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
 }
\ No newline at end of file