diff --git a/vllm/engine/llm_engine.py b/vllm/engine/llm_engine.py
index e33d8aa2a2131..f79b5e84f49ac 100644
--- a/vllm/engine/llm_engine.py
+++ b/vllm/engine/llm_engine.py
@@ -12,8 +12,8 @@
 from vllm.outputs import RequestOutput
 from vllm.sampling_params import SamplingParams
 from vllm.sequence import (SamplerOutput, Sequence, SequenceGroup,
-                           SequenceGroupMetadata, SequenceGroupOutputs,
-                           SequenceOutputs, SequenceStatus)
+                           SequenceGroupMetadata, SequenceGroupOutput,
+                           SequenceOutput, SequenceStatus)
 from vllm.transformers_utils.tokenizer import (detokenize_incrementally,
                                                get_tokenizer)
 from vllm.utils import Counter
@@ -363,7 +363,7 @@ def _check_beam_search_early_stopping(
         return current_worst_score >= highest_attainable_score
 
     def _process_sequence_group_outputs(self, seq_group: SequenceGroup,
-                                        outputs: SequenceGroupOutputs) -> None:
+                                        outputs: SequenceGroupOutput) -> None:
         # Process prompt logprobs
         prompt_logprobs = outputs.prompt_logprobs
         if prompt_logprobs is not None:
@@ -384,7 +384,7 @@ def _process_sequence_group_outputs(self, seq_group: SequenceGroup,
 
         # Process the child samples for each parent sequence
         for parent in parent_seqs:
-            child_samples: List[SequenceOutputs] = parent_child_dict[
+            child_samples: List[SequenceOutput] = parent_child_dict[
                 parent.seq_id]
             if len(child_samples) == 0:
                 # This parent sequence has no children samples. Remove
diff --git a/vllm/model_executor/layers/sampler.py b/vllm/model_executor/layers/sampler.py
index c874ec5921155..b545587fd2044 100644
--- a/vllm/model_executor/layers/sampler.py
+++ b/vllm/model_executor/layers/sampler.py
@@ -9,7 +9,7 @@
     tensor_model_parallel_all_gather)
 from vllm.sampling_params import SamplingParams, SamplingType
 from vllm.sequence import (PromptLogprobs, SampleLogprobs, SamplerOutput,
-                           SequenceData, SequenceGroupOutputs, SequenceOutputs)
+                           SequenceData, SequenceGroupOutput, SequenceOutput)
 
 _SAMPLING_EPS = 1e-5
 
@@ -641,7 +641,7 @@ def _build_sampler_output(
                                                       next_token_ids,
                                                       group_sample_logprobs):
             seq_outputs.append(
-                SequenceOutputs(seq_ids[parent_id], next_token_id, logprobs))
+                SequenceOutput(seq_ids[parent_id], next_token_id, logprobs))
         sampler_output.append(
-            SequenceGroupOutputs(seq_outputs, group_prompt_logprobs))
+            SequenceGroupOutput(seq_outputs, group_prompt_logprobs))
     return sampler_output
diff --git a/vllm/sequence.py b/vllm/sequence.py
index ecfaee6e8c3d6..7d36eeac0aa02 100644
--- a/vllm/sequence.py
+++ b/vllm/sequence.py
@@ -352,7 +352,7 @@ def __init__(
         self.block_tables = block_tables
 
 
-class SequenceOutputs:
+class SequenceOutput:
     """The model output associated with a sequence.
 
     Args:
@@ -374,40 +374,40 @@ def __init__(
         self.logprobs = logprobs
 
     def __repr__(self) -> str:
-        return (f"SequenceOutputs(parent_seq_id={self.parent_seq_id}, "
+        return (f"SequenceOutput(parent_seq_id={self.parent_seq_id}, "
                 f"output_token={self.output_token}, "
                 f"logprobs={self.logprobs})")
 
     def __eq__(self, other: object) -> bool:
-        if not isinstance(other, SequenceOutputs):
+        if not isinstance(other, SequenceOutput):
             raise NotImplementedError()
         return (self.parent_seq_id == other.parent_seq_id
                 and self.output_token == other.output_token
                 and self.logprobs == other.logprobs)
 
 
-class SequenceGroupOutputs:
-    """The model outputs associated with a sequence group."""
+class SequenceGroupOutput:
+    """The model output associated with a sequence group."""
 
     def __init__(
         self,
-        samples: List[SequenceOutputs],
+        samples: List[SequenceOutput],
         prompt_logprobs: Optional[PromptLogprobs],
     ) -> None:
         self.samples = samples
         self.prompt_logprobs = prompt_logprobs
 
     def __repr__(self) -> str:
-        return (f"SequenceGroupOutputs(samples={self.samples}, "
+        return (f"SequenceGroupOutput(samples={self.samples}, "
                 f"prompt_logprobs={self.prompt_logprobs})")
 
     def __eq__(self, other: object) -> bool:
-        if not isinstance(other, SequenceGroupOutputs):
+        if not isinstance(other, SequenceGroupOutput):
             raise NotImplementedError()
         return (self.samples == other.samples
                 and self.prompt_logprobs == other.prompt_logprobs)
 
 
-# For each sequence group, we generate a list of SequenceOutputs object,
+# For each sequence group, we generate a list of SequenceOutput object,
 # each of which contains one possible candidate for the next token.
-SamplerOutput = List[SequenceGroupOutputs]
+SamplerOutput = List[SequenceGroupOutput]