diff --git a/scripts/export/export_to_trt_llm.py b/scripts/export/export_to_trt_llm.py
index 6b246131b69e..d9e846547c68 100644
--- a/scripts/export/export_to_trt_llm.py
+++ b/scripts/export/export_to_trt_llm.py
@@ -44,7 +44,7 @@ def get_args(argv):
     parser.add_argument(
         "-mr", "--model_repository", required=True, default=None, type=str, help="Folder for the trt-llm model files"
     )
-    parser.add_argument("-ng", "--num_gpus", default=1, type=int, help="Number of GPUs for the deployment")
+    parser.add_argument("-ng", "--num_gpus", default=None, type=int, help="Number of GPUs for the deployment")
     parser.add_argument("-tps", "--tensor_parallelism_size", default=1, type=int, help="Tensor parallelism size")
     parser.add_argument("-pps", "--pipeline_parallelism_size", default=1, type=int, help="Pipeline parallelism size")
     parser.add_argument(
@@ -64,7 +64,14 @@ def get_args(argv):
         "-mpet", "--max_prompt_embedding_table_size", default=None, type=int, help="Max prompt embedding table size"
     )
     parser.add_argument(
-        "-npkc", "--no_paged_kv_cache", default=False, action='store_true', help="Enable paged kv cache."
+        "-upe",
+        "--use_parallel_embedding",
+        default=False,
+        action='store_true',
+        help="Use parallel embedding.",
+    )
+    parser.add_argument(
+        "-npkc", "--no_paged_kv_cache", default=False, action='store_true', help="Disable paged kv cache."
     )
     parser.add_argument(
         "-drip",
@@ -183,6 +190,7 @@ def nemo_export_trt_llm(argv):
             max_num_tokens=args.max_num_tokens,
             opt_num_tokens=args.opt_num_tokens,
             max_prompt_embedding_table_size=args.max_prompt_embedding_table_size,
+            use_parallel_embedding=args.use_parallel_embedding,
             paged_kv_cache=(not args.no_paged_kv_cache),
             remove_input_padding=(not args.disable_remove_input_padding),
             dtype=args.dtype,
@@ -191,6 +199,7 @@ def nemo_export_trt_llm(argv):
             max_lora_rank=args.max_lora_rank,
             fp8_quantized=args.export_fp8_quantized,
             fp8_kvcache=args.use_fp8_kv_cache,
+            load_model=False,
         )
 
         LOGGER.info("Export is successful.")