diff --git a/src/transformers/generation/candidate_generator.py b/src/transformers/generation/candidate_generator.py
index a958228d9be..52371d94dc5 100644
--- a/src/transformers/generation/candidate_generator.py
+++ b/src/transformers/generation/candidate_generator.py
@@ -150,6 +150,12 @@ def __init__(
         self.generation_config.return_dict_in_generate = True
         self.generation_config.output_scores = True
 
+        # Disable sampling -- this implementation of assisted generation/speculative decoding uses the assistant
+        # greedily to maximize matches. Disables sampling-related flags to prevent warnings
+        self.generation_config.do_sample = False
+        for attr in ("temperature", "top_p", "min_p", "typical_p", "top_k", "epsilon_cutoff", "eta_cutoff"):
+            setattr(self.generation_config, attr, None)
+
         # avoid unnecessary warnings that min_length is larger than max_new_tokens
         # remove the `MinLengthLogitsProcessor` if exists (NOTE: no need to check for `MinNewTokensLogitsProcessor`)
         self.main_model_min_length = self.generation_config.min_length
diff --git a/src/transformers/generation/configuration_utils.py b/src/transformers/generation/configuration_utils.py
index 85fcc055948..2bdf20c6861 100644
--- a/src/transformers/generation/configuration_utils.py
+++ b/src/transformers/generation/configuration_utils.py
@@ -496,6 +496,11 @@ def validate(self, is_init=False):
                     greedy_wrong_parameter_msg.format(flag_name="top_p", flag_value=self.top_p),
                     UserWarning,
                 )
+            if self.min_p is not None:
+                warnings.warn(
+                    greedy_wrong_parameter_msg.format(flag_name="min_p", flag_value=self.min_p),
+                    UserWarning,
+                )
             if self.typical_p is not None and self.typical_p != 1.0:
                 warnings.warn(
                     greedy_wrong_parameter_msg.format(flag_name="typical_p", flag_value=self.typical_p),