diff --git a/tensorflow/lite/toco/graph_transformations/identify_lstm.cc b/tensorflow/lite/toco/graph_transformations/identify_lstm.cc
index 089ecee959a..65dbb8a1766 100644
--- a/tensorflow/lite/toco/graph_transformations/identify_lstm.cc
+++ b/tensorflow/lite/toco/graph_transformations/identify_lstm.cc
@@ -147,12 +147,26 @@ bool MatchOperatorInputs(const Operator& op, const Model& model,
   if (final_output_mul->type != OperatorType::kMul) {
     return ::tensorflow::Status::OK();
   }
+  // final_output_mul->outputs[0] would be one of the two outputs of our
+  // LstmCell. Exit if it does not already have a data type.
+  // We won't be able to propagate data types through a fused LstmCell.
+  if (model->GetArray(final_output_mul->outputs[0]).data_type ==
+      ArrayDataType::kNone) {
+    return ::tensorflow::Status::OK();
+  }
   Operator *state_output_tanh, *fc_output_sig;
   if (!MatchOperatorInputs(*final_output_mul, *model, OperatorType::kTanh,
                            &state_output_tanh, OperatorType::kLogistic,
                            &fc_output_sig)) {
     return ::tensorflow::Status::OK();
   }
+  // state_output_tanh->inputs[0] would be one of the two outputs of our
+  // LstmCell. Exit if it does not already have a data type.
+  // We won't be able to propagate data types through a fused LstmCell.
+  if (model->GetArray(state_output_tanh->inputs[0]).data_type ==
+      ArrayDataType::kNone) {
+    return ::tensorflow::Status::OK();
+  }
 
   // State output TanH
   // (We don't count an operator as ID'd until we verify it has the correct
@@ -262,11 +276,15 @@ bool MatchOperatorInputs(const Operator& op, const Model& model,
       lstm_cell_op->outputs[LstmCellOperator::ACTIV_OUTPUT]));
   const string& concat_temp_array_name =
       AvailableArrayName(*model, base_name + "concat_temp");
-  model->GetOrCreateArray(concat_temp_array_name);
+  auto& concat_temp_array = model->GetOrCreateArray(concat_temp_array_name);
+  concat_temp_array.data_type =
+      model->GetArray(concat_inputs->outputs[0]).data_type;
   lstm_cell_op->outputs[LstmCellOperator::CONCAT_TEMP] = concat_temp_array_name;
   const string& activ_temp_array_name =
       AvailableArrayName(*model, base_name + "activ_temp");
-  model->GetOrCreateArray(activ_temp_array_name);
+  auto& activ_temp_array = model->GetOrCreateArray(activ_temp_array_name);
+  activ_temp_array.data_type =
+      model->GetArray(fully_connected->outputs[0]).data_type;
   lstm_cell_op->outputs[LstmCellOperator::ACTIV_TEMP] = activ_temp_array_name;
   AddMessageF("Created temp outputs %s and %s on operator %s",
               concat_temp_array_name, activ_temp_array_name,
diff --git a/tensorflow/lite/toco/graph_transformations/propagate_array_data_types.cc b/tensorflow/lite/toco/graph_transformations/propagate_array_data_types.cc
index 7aec6728da6..d546ff4ec0d 100644
--- a/tensorflow/lite/toco/graph_transformations/propagate_array_data_types.cc
+++ b/tensorflow/lite/toco/graph_transformations/propagate_array_data_types.cc
@@ -266,6 +266,14 @@ void SetDataTypeForAllOutputs(Model* model, Operator* op,
       model->GetArray(op->outputs[1]).data_type = unique_op->idx_out_type;
       break;
     }
+    case OperatorType::kLstmCell: {
+      // It's tricky to propagate data types through a LstmCell, as that has
+      // multiple inputs and outputs, and there are quantized cases with
+      // mixed (8bit vs 16bit) cases. Fortunately, that should never be needed,
+      // as the data formats, such as TFLITE, that have LstmCell nodes, also
+      // have data type fields for all their arrays.
+      break;
+    }
     default: {
       // These operators produce outputs with the same type as their 1st input
       CHECK_GT(op->inputs.size(), 0);
diff --git a/tensorflow/lite/toco/toco_tooling.cc b/tensorflow/lite/toco/toco_tooling.cc
index 55a454e66de..61dca56d23e 100644
--- a/tensorflow/lite/toco/toco_tooling.cc
+++ b/tensorflow/lite/toco/toco_tooling.cc
@@ -178,6 +178,23 @@ void SetFinalDataTypeOnInputs(const TocoFlags& toco_flags, Model* model) {
       // Ignore non-real data types.
       continue;
     }
+    // The enum value QUANTIZED_UINT8 for --inference_type and
+    // --inference_input_type has long meant just 'QUANTIZED', being used as
+    // well in mixed 8-bit / 16-bit quantized models. However,
+    // ConvertIODataTypeToArrayDataType still interpretes it as meaning 8bit,
+    // and people have run into issues in the situation where they have an
+    // already mixed 8-bit / 16-bit quantized model in TFLITE format and
+    // want to run it again through toco, without having to re-specify all the
+    // extra array info that was used in the (complicated) process of initially
+    // quantizing that model. In order to have --inference_type=QUANTIZED_UINT8
+    // just work in that case, we implement the logic that when an array is
+    // already quantized, if  --inference_type is quantized (so we're not
+    // asking to dequantize here), no change of quantized data type is to be
+    // recorded.
+    if (array->data_type != toco::ArrayDataType::kFloat &&
+        type != toco::ArrayDataType::kFloat) {
+      continue;
+    }
 
     array->final_data_type = type;
   }