diff --git a/scripts/grpo_demo_llama3_qwen2.py b/scripts/grpo_demo_llama3_qwen2.py
index a94f3e726..58544b059 100644
--- a/scripts/grpo_demo_llama3_qwen2.py
+++ b/scripts/grpo_demo_llama3_qwen2.py
@@ -46,7 +46,6 @@
 from tunix.models.qwen2 import model as qwen2_lib
 from tunix.models.qwen2 import params as qwen2_params
 from tunix.rl import rl_cluster as rl_cluster_lib
-from tunix.rl.grpo import grpo_learner
 from tunix.rl.rollout import base_rollout
 from tunix.sft import metrics_logger
 from tunix.sft import profiler
@@ -243,11 +242,36 @@
     required=False,
     help="Name of dataset, required when data_source is tfds",
 )
-
+parser.add_argument(
+    "--agentic-mode",
+    type=bool,
+    default=False,
+    required=False,
+    help="Whether to use agentic mode.",
+)
+parser.add_argument(
+    "--agentic-max-concurrency",
+    type=int,
+    default=4,
+    required=False,
+    help="Max concurrency for agentic mode.",
+)
+parser.add_argument(
+    "--agentic-off-policy-steps",
+    type=int,
+    default=0,
+    required=False,
+    help="Number of off-policy steps for agentic mode.",
+)
 
 # Parse arguments
 args = parser.parse_args()
 
+if args.agentic_mode:
+  from tunix.rl.experimental import agentic_grpo_learner as grpo_learner  # pylint: disable=g-import-not-at-top
+else:
+  from tunix.rl import grpo_learner  # pylint: disable=g-import-not-at-top
+
 
 def validata_args():
   if args.data_source == "tfds":
@@ -1100,12 +1124,22 @@ def get_rollout_config(engine: str) -> base_rollout.RolloutConfig:
     rollout_config=get_rollout_config(args.rollout_engine),
 )
 
-grpo_config = grpo_learner.GRPOConfig(
-    num_generations=NUM_GENERATIONS,
-    num_iterations=NUM_ITERATIONS,
-    beta=BETA,
-    epsilon=EPSILON,
-)
+if args.agentic_mode:
+  grpo_config = grpo_learner.GRPOConfig(
+      num_generations=NUM_GENERATIONS,
+      num_iterations=NUM_ITERATIONS,
+      beta=BETA,
+      epsilon=EPSILON,
+      max_concurrency=args.agentic_max_concurrency,
+      off_policy_steps=args.agentic_off_policy_steps,
+  )
+else:
+  grpo_config = grpo_learner.GRPOConfig(
+      num_generations=NUM_GENERATIONS,
+      num_iterations=NUM_ITERATIONS,
+      beta=BETA,
+      epsilon=EPSILON,
+  )
 
 
 # RL cluster
@@ -1161,7 +1195,7 @@ def get_rollout_config(engine: str) -> base_rollout.RolloutConfig:
 
 show_hbm_usage("Right before training")
 with training_mesh:
-  grpo_trainer.train(train_dataset, eval_ds=val_dataset)
+  grpo_trainer.train(train_dataset, val_dataset)
 
 # Load checkpoint first.