diff --git a/tensorrt_llm/_torch/pyexecutor/_util.py b/tensorrt_llm/_torch/pyexecutor/_util.py
index 4b04c99644b..3f27c34e864 100644
--- a/tensorrt_llm/_torch/pyexecutor/_util.py
+++ b/tensorrt_llm/_torch/pyexecutor/_util.py
@@ -828,7 +828,7 @@ def create_torch_sampler_args(mapping: Mapping, *, max_seq_len: int,
                               max_batch_size: int,
                               speculative_config: SpeculativeConfig,
                               max_beam_width: int,
-                              disable_flash_infer_sampling: bool):
+                              disable_flashinfer_sampling: bool):
     max_num_sequences = max_batch_size * mapping.pp_size
     max_draft_len = (0 if speculative_config is None else
                      speculative_config.max_draft_len)
@@ -841,7 +841,7 @@ def create_torch_sampler_args(mapping: Mapping, *, max_seq_len: int,
         max_total_draft_tokens=max_total_draft_tokens,
         max_num_sequences=max_num_sequences,
         max_beam_width=max_beam_width,
-        disable_flash_infer_sampling=disable_flash_infer_sampling,
+        disable_flashinfer_sampling=disable_flashinfer_sampling,
     )
 
 
@@ -857,7 +857,7 @@ def instantiate_sampler(
     speculative_config: SpeculativeConfig,
     decoding_config: trtllm.DecodingConfig,
     kv_cache_config: KvCacheConfig,
-    disable_flash_infer_sampling: bool,
+    disable_flashinfer_sampling: bool,
 ):
     sampler_args = create_torch_sampler_args(
         mapping,
@@ -865,7 +865,7 @@ def instantiate_sampler(
         max_batch_size=max_batch_size,
         speculative_config=speculative_config,
         max_beam_width=max_beam_width,
-        disable_flash_infer_sampling=disable_flash_infer_sampling,
+        disable_flashinfer_sampling=disable_flashinfer_sampling,
     )
     decoding_mode = get_decoding_mode(decoding_config=decoding_config,
                                       max_beam_width=max_beam_width)
diff --git a/tensorrt_llm/_torch/pyexecutor/py_executor_creator.py b/tensorrt_llm/_torch/pyexecutor/py_executor_creator.py
index 923599562ce..3605369a7f6 100644
--- a/tensorrt_llm/_torch/pyexecutor/py_executor_creator.py
+++ b/tensorrt_llm/_torch/pyexecutor/py_executor_creator.py
@@ -533,7 +533,7 @@ def drafting_loop_wrapper(model):
             speculative_config=spec_config,
             decoding_config=decoding_config,
             kv_cache_config=kv_cache_config,
-            disable_flash_infer_sampling=llm_args._disable_flash_infer_sampling,
+            disable_flashinfer_sampling=llm_args.disable_flashinfer_sampling,
         )
         logger.info(f"Using Sampler: {type(sampler).__name__}")
 
diff --git a/tensorrt_llm/_torch/pyexecutor/sampler.py b/tensorrt_llm/_torch/pyexecutor/sampler.py
index 2dea9a25537..5feacbe6ca4 100644
--- a/tensorrt_llm/_torch/pyexecutor/sampler.py
+++ b/tensorrt_llm/_torch/pyexecutor/sampler.py
@@ -616,7 +616,7 @@ class Args:
         max_num_sequences: int
         max_beam_width: int
         max_total_draft_tokens: int
-        disable_flash_infer_sampling: bool = False
+        disable_flashinfer_sampling: bool = False
 
     def __init__(self, args: Args):
         self.max_seq_len = args.max_seq_len
@@ -652,7 +652,7 @@ def __init__(self, args: Args):
             }
 
         self._grouped_sampler_cls: Type[GroupedStrategySampler]
-        if IS_FLASHINFER_AVAILABLE and not args.disable_flash_infer_sampling:
+        if IS_FLASHINFER_AVAILABLE and not args.disable_flashinfer_sampling:
             from .sampling_utils_flashinfer import FlashInferGroupedStrategySampler
 
             self._grouped_sampler_cls = FlashInferGroupedStrategySampler
diff --git a/tensorrt_llm/llmapi/llm_args.py b/tensorrt_llm/llmapi/llm_args.py
index 58b05edad2b..337127fa4ae 100644
--- a/tensorrt_llm/llmapi/llm_args.py
+++ b/tensorrt_llm/llmapi/llm_args.py
@@ -2707,8 +2707,12 @@ class TorchLlmArgs(BaseLlmArgs):
     # PrivateVars
     _quant_config: Optional[QuantConfig] = PrivateAttr(default=None)
 
-    _disable_flash_infer_sampling: bool = PrivateAttr(default=True)
-    """Unless this is set to False, FlashInfer.sampling is not used, even if available."""
+    disable_flashinfer_sampling: bool = Field(
+        default=True,
+        description=
+        "Disable the use of FlashInfer.sampling. This option is likely to be removed in the future.",
+        status="prototype",
+    )
 
     @property
     def quant_config(self) -> QuantConfig:
diff --git a/tests/unittest/_torch/sampler/test_torch_sampler.py b/tests/unittest/_torch/sampler/test_torch_sampler.py
index cc2e52904ce..a782e8eb400 100644
--- a/tests/unittest/_torch/sampler/test_torch_sampler.py
+++ b/tests/unittest/_torch/sampler/test_torch_sampler.py
@@ -1077,7 +1077,7 @@ def _build_sampler(
                 max_beam_width=1,  # currently the only supported value
                 max_num_sequences=num_seq_slots,
                 max_total_draft_tokens=max_draft_len,
-                disable_flash_infer_sampling=(not use_flashinfer),
+                disable_flashinfer_sampling=(not use_flashinfer),
             )
         )
 
diff --git a/tests/unittest/api_stability/references/llm.yaml b/tests/unittest/api_stability/references/llm.yaml
index c08ec37c119..18308ab290e 100644
--- a/tests/unittest/api_stability/references/llm.yaml
+++ b/tests/unittest/api_stability/references/llm.yaml
@@ -107,6 +107,10 @@ methods:
         annotation: bool
         default: False
         status: beta
+      disable_flashinfer_sampling:
+        annotation: bool
+        default: False
+        status: prototype
       moe_config:
         annotation: tensorrt_llm.llmapi.llm_args.MoeConfig
         status: beta