diff --git a/examples/text-generation/run_generation.py b/examples/text-generation/run_generation.py
index ab308e7023..813f40d790 100644
--- a/examples/text-generation/run_generation.py
+++ b/examples/text-generation/run_generation.py
@@ -231,11 +231,19 @@ def setup_parser(parser):
         action="store_true",
         help="Whether to enable Habana Flash Attention, provided that the model supports it.",
     )
+    parser.add_argument(
+        "--torch_compile",
+        action="store_true",
+        help="Whether to use torch compiled model or not.",
+    )
     parser.add_argument("--temperature", default=1.0, type=float, help="Temperature value for text generation")
     parser.add_argument("--top_p", default=1.0, type=float, help="Top_p value for generating text via sampling")
 
     args = parser.parse_args()
 
+    if args.torch_compile:
+        args.use_hpu_graphs = False
+
     if not args.use_hpu_graphs:
         args.limit_hpu_graphs = False
 
@@ -247,6 +255,10 @@ def main():
     args = setup_parser(parser)
     model, tokenizer, generation_config = initialize_model(args, logger)
 
+    use_lazy_mode = True
+    if args.torch_compile and model.config.model_type == "llama":
+        use_lazy_mode = False
+
     import habana_frameworks.torch.hpu as torch_hpu
 
     if args.dataset_name is None:
@@ -299,7 +311,7 @@ def generate(size=None, reduce_recompile=False):
             outputs = model.generate(
                 **input_tokens,
                 generation_config=generation_config,
-                lazy_mode=True,
+                lazy_mode=use_lazy_mode,
                 hpu_graphs=args.use_hpu_graphs,
                 profiling_steps=args.profiling_steps,
                 profiling_warmup_steps=args.profiling_warmup_steps,
@@ -479,7 +491,7 @@ def generate_dataset(batch):
             outputs = model.generate(
                 **batch,
                 generation_config=generation_config,
-                lazy_mode=True,
+                lazy_mode=use_lazy_mode,
                 hpu_graphs=args.use_hpu_graphs,
                 profiling_steps=args.profiling_steps,
                 profiling_warmup_steps=args.profiling_warmup_steps,
diff --git a/examples/text-generation/utils.py b/examples/text-generation/utils.py
index 5c03de7dc6..46ef9fa1f6 100644
--- a/examples/text-generation/utils.py
+++ b/examples/text-generation/utils.py
@@ -115,7 +115,7 @@ def setup_env(args):
     check_min_version("4.34.0")
     check_optimum_habana_min_version("1.9.0.dev0")
 
-    if args.global_rank == 0:
+    if args.global_rank == 0 and not args.torch_compile:
         os.environ.setdefault("GRAPH_VISUALIZATION", "true")
         shutil.rmtree(".graph_dumps", ignore_errors=True)
 
@@ -151,6 +151,11 @@ def patch_scoped_linear_all_reduce(model):
         patch_scoped_linear_all_reduce(module)
 
 
+def get_torch_compiled_model(model):
+    model.model = torch.compile(model.model, backend="aot_hpu_inference_backend")
+    return model
+
+
 def setup_model(args, model_dtype, model_kwargs, logger):
     logger.info("Single-device run.")
 
@@ -170,6 +175,10 @@ def setup_model(args, model_dtype, model_kwargs, logger):
             model = wrap_in_hpu_graph(model, hash_with_views=not args.skip_hash_with_views)
         else:
             model = wrap_in_hpu_graph(model)
+
+    if args.torch_compile and model.config.model_type == "llama":
+        model = get_torch_compiled_model(model)
+
     return model
 
 
diff --git a/tests/test_text_generation_example.py b/tests/test_text_generation_example.py
index faae5b79db..20ff84ac1d 100644
--- a/tests/test_text_generation_example.py
+++ b/tests/test_text_generation_example.py
@@ -30,6 +30,9 @@
             ("meta-llama/Llama-2-70b-hf", 58.2750262232098),
             ("facebook/opt-66b", 28.16154122335556),
         ],
+        "torch_compile": [
+            ("meta-llama/Llama-2-7b-hf", 8.95169640119334),
+        ],
     }
 else:
     # Gaudi1 CI baselines
@@ -50,13 +53,22 @@
         "deepspeed": [
             ("bigscience/bloomz-7b1", 27.34439410425298),
         ],
+        "torch_compile": [],
     }
 
 
-def _test_text_generation(model_name: str, baseline: float, token: str, deepspeed: bool = False, world_size: int = 8):
+def _test_text_generation(
+    model_name: str,
+    baseline: float,
+    token: str,
+    deepspeed: bool = False,
+    world_size: int = 8,
+    torch_compile: bool = False,
+):
     command = ["python3"]
     path_to_example_dir = Path(__file__).resolve().parent.parent / "examples"
 
+    deepspeed = deepspeed and not torch_compile
     if deepspeed:
         command += [
             f"{path_to_example_dir / 'gaudi_spawn.py'}",
@@ -68,11 +80,22 @@ def _test_text_generation(model_name: str, baseline: float, token: str, deepspee
         f"{path_to_example_dir / 'text-generation' / 'run_generation.py'}",
         f"--model_name_or_path {model_name}",
         "--batch_size 1",
-        "--use_hpu_graphs",
         "--use_kv_cache",
         "--max_new_tokens 100",
     ]
 
+    if torch_compile:
+        command += [
+            "--attn_softmax_bf16",
+            "--reuse_cache",
+            "--trim_logits",
+            "--torch_compile",
+        ]
+    else:
+        command += [
+            "--use_hpu_graphs",
+        ]
+
     if not deepspeed:
         command.append("--bf16")
 
@@ -115,3 +138,11 @@ def test_text_generation_bf16(model_name: str, baseline: float, token: str):
 def test_text_generation_deepspeed(model_name: str, baseline: float, token: str):
     world_size = 2 if "opt-66b" in model_name else 8
     _test_text_generation(model_name, baseline, token, deepspeed=True, world_size=world_size)
+
+
+@pytest.mark.parametrize("model_name, baseline", MODELS_TO_TEST["torch_compile"])
+def test_text_generation_torch_compile(model_name: str, baseline: float, token: str):
+    os.environ["PT_ENABLE_INT64_SUPPORT"] = "1"
+    os.environ["PT_HPU_LAZY_MODE"] = "0"
+    os.environ["WORLD_SIZE"] = "0"
+    _test_text_generation(model_name, baseline, token, torch_compile=True)