diff --git a/examples/offline_inference/run_one_batch.py b/examples/offline_inference/run_one_batch.py
new file mode 100644
index 000000000..d7692c563
--- /dev/null
+++ b/examples/offline_inference/run_one_batch.py
@@ -0,0 +1,112 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from __future__ import annotations
+
+from vllm import LLM, EngineArgs
+from vllm.config import ProfilerConfig
+from vllm.utils.argparse_utils import FlexibleArgumentParser
+
+DEFAULT_MAX_TOKENS = 16
+
+
+def create_parser() -> FlexibleArgumentParser:
+    parser = FlexibleArgumentParser()
+    EngineArgs.add_cli_args(parser)
+    parser.set_defaults(model="meta-llama/Llama-3.2-1B-Instruct")
+
+    batch_group = parser.add_argument_group("Batch parameters")
+    batch_group.add_argument("--batch-size", type=int, default=1)
+    batch_group.add_argument("--prompt-size", type=int, default=128)
+    batch_group.add_argument("--prompt-prefix", type=str, default="Hello, my name is")
+
+    profile_group = parser.add_argument_group("Profiling parameters")
+    profile_group.add_argument(
+        "--profile",
+        choices=["none", "prefill", "decode", "both"],
+        default="none",
+    )
+    profile_group.add_argument(
+        "--profile-dir",
+        type=str,
+        default="",
+        help="Required when --profile is not 'none'.",
+    )
+
+    return parser
+
+
+def _build_prompt(prefix: str, prompt_size: int) -> str:
+    if prompt_size <= 0:
+        return ""
+    if not prefix:
+        prefix = " "
+    if len(prefix) >= prompt_size:
+        return prefix[:prompt_size]
+    repeat_count = (prompt_size + len(prefix) - 1) // len(prefix)
+    return (prefix * repeat_count)[:prompt_size]
+
+
+def _build_profiler_config(
+    profile: str, profile_dir: str, max_tokens: int
+) -> ProfilerConfig | None:
+    if profile == "none":
+        return None
+    if not profile_dir:
+        raise ValueError("--profile-dir must be set when profiling is enabled.")
+    if profile == "prefill":
+        delay_iterations = 0
+        max_iterations = 1
+    elif profile == "decode":
+        delay_iterations = 1
+        max_iterations = max(1, max_tokens)
+    else:
+        delay_iterations = 0
+        max_iterations = 0
+
+    return ProfilerConfig(
+        profiler="torch",
+        torch_profiler_dir=profile_dir,
+        delay_iterations=delay_iterations,
+        max_iterations=max_iterations,
+    )
+
+
+def main(args: dict) -> None:
+    max_tokens = DEFAULT_MAX_TOKENS
+    batch_size = args.pop("batch_size")
+    prompt_size = args.pop("prompt_size")
+    prompt_prefix = args.pop("prompt_prefix")
+    profile = args.pop("profile")
+    profile_dir = args.pop("profile_dir")
+
+    profiler_config = _build_profiler_config(profile, profile_dir, max_tokens)
+    if profiler_config is not None:
+        args["profiler_config"] = profiler_config
+
+    llm = LLM(**args)
+
+    sampling_params = llm.get_default_sampling_params()
+    sampling_params.max_tokens = max_tokens
+    sampling_params.min_tokens = max_tokens
+    sampling_params.ignore_eos = True
+
+    prompt = _build_prompt(prompt_prefix, prompt_size)
+    prompts = [prompt] * batch_size
+
+    if profile != "none":
+        llm.start_profile()
+    outputs = llm.generate(prompts, sampling_params)
+    if profile != "none":
+        llm.stop_profile()
+
+    print("-" * 50)
+    for output in outputs:
+        generated_text = output.outputs[0].text
+        print(f"Prompt: {output.prompt!r}\nGenerated text: {generated_text!r}")
+        print("-" * 50)
+
+
+if __name__ == "__main__":
+    parser = create_parser()
+    main(vars(parser.parse_args()))