diff --git a/python/sglang/bench_serving.py b/python/sglang/bench_serving.py
index 936950908..e90e7f754 100644
--- a/python/sglang/bench_serving.py
+++ b/python/sglang/bench_serving.py
@@ -1753,6 +1753,8 @@ async def benchmark(
     max_concurrency: Optional[int],
     disable_tqdm: bool,
     lora_names: List[str],
+    lora_request_distribution: Optional[str],
+    lora_zipf_alpha: Optional[float],
     extra_request_body: Dict[str, Any],
     profile: bool,
     pd_separated: bool = False,
@@ -1893,11 +1895,30 @@ async def benchmark(
     else:
         request_generator = get_request(input_requests, request_rate)
 
+    # Prepare LoRA request distribution parameters
+    if lora_request_distribution == "distinct":
+        lora_idx = 0
+    elif lora_request_distribution == "skewed":
+        weights = np.array([lora_zipf_alpha**-i for i in range(len(lora_names))])
+        lora_probs = weights / np.sum(weights)
+    else:
+        lora_idx = None
+        lora_probs = None
+
     pbar = None if disable_tqdm else tqdm(total=pbar_total)
     async for request in request_generator:
         if lora_names is not None and len(lora_names) != 0:
-            idx = random.randint(0, len(lora_names) - 1)
-            lora_name = lora_names[idx]
+            if lora_request_distribution == "uniform":
+                lora_name = random.choice(lora_names)
+            elif lora_request_distribution == "distinct":
+                lora_name = lora_names[lora_idx]
+                lora_idx = (lora_idx + 1) % len(lora_names)
+            else:
+                assert (
+                    lora_request_distribution == "skewed"
+                ), f"Unexpected lora_request_distribution: {lora_request_distribution}. Expected 'skewed'."
+
+                lora_name = np.random.choice(lora_names, p=lora_probs)
         else:
             lora_name = None
 
@@ -2289,6 +2310,15 @@ def run_benchmark(args_: argparse.Namespace):
             not args.tokenize_prompt
         ), "`--tokenize-prompt` not compatible with image dataset"
 
+    if args.lora_request_distribution in ["distinct", "skewed"]:
+        assert (
+            args.lora_name is not None and len(args.lora_name) > 1
+        ), "More than 1 LoRA adapter must be specified via --lora-name to use 'distinct' or 'skewed' request distribution."
+
+    assert (
+        args.lora_zipf_alpha > 1
+    ), f"Got invalid value for --lora-zipf-alpha of {args.lora_zipf_alpha}. It must be greater than 1."
+
     print(f"{args}\n")
 
     # Read dataset
@@ -2302,6 +2332,17 @@ def run_benchmark(args_: argparse.Namespace):
     if not hasattr(args, "flush_cache"):
         args.flush_cache = False
 
+    # Prepare LoRA arguments
+    lora_request_distribution = (
+        args.lora_request_distribution if args.lora_name is not None else None
+    )
+
+    lora_zipf_alpha = (
+        args.lora_zipf_alpha
+        if args.lora_name is not None and args.lora_request_distribution == "skewed"
+        else None
+    )
+
     return asyncio.run(
         benchmark(
             backend=backend,
@@ -2314,6 +2355,8 @@ def run_benchmark(args_: argparse.Namespace):
             max_concurrency=args.max_concurrency,
             disable_tqdm=args.disable_tqdm,
             lora_names=args.lora_name,
+            lora_request_distribution=lora_request_distribution,
+            lora_zipf_alpha=lora_zipf_alpha,
             extra_request_body=extra_request_body,
             profile=args.profile,
             pd_separated=args.pd_separated,
@@ -2551,6 +2594,27 @@ if __name__ == "__main__":
         action=LoRAPathAction,
         help="The names of LoRA adapters. You can provide a list of names in the format {name} {name} {name}...",
     )
+    parser.add_argument(
+        "--lora-request-distribution",
+        type=str,
+        default="uniform",
+        choices=[
+            "uniform",
+            "distinct",
+            "skewed",
+        ],
+        help="What distribution to sample the LoRA adapters specified in --lora-name. Borrowed from the Punica paper. "
+        "'distinct' distribution means selecting a new LoRA adapter for every request. "
+        "'skewed' distribution follows the Zipf distribution, where the number of requests "
+        "to model i specified in --lora-name is α times the number of requests for model i+1, "
+        "where α > 1.",
+    )
+    parser.add_argument(
+        "--lora-zipf-alpha",
+        type=float,
+        default=1.5,
+        help="The parameter to use for the Zipf distribution when --lora-request-distribution='skewed'.",
+    )
     parser.add_argument(
         "--prompt-suffix",
         type=str,
diff --git a/python/sglang/test/test_utils.py b/python/sglang/test/test_utils.py
index 3eb6093b1..5b6ed7766 100644
--- a/python/sglang/test/test_utils.py
+++ b/python/sglang/test/test_utils.py
@@ -806,6 +806,8 @@ def get_benchmark_args(
     device="auto",
     pd_separated: bool = False,
     lora_name=None,
+    lora_request_distribution="uniform",
+    lora_zipf_alpha=1.5,
 ):
     return SimpleNamespace(
         backend="sglang",
@@ -834,6 +836,8 @@ def get_benchmark_args(
         apply_chat_template=False,
         profile=None,
         lora_name=lora_name,
+        lora_request_distribution=lora_request_distribution,
+        lora_zipf_alpha=lora_zipf_alpha,
         prompt_suffix="",
         device=device,
         pd_separated=pd_separated,