diff --git a/vllm/model_executor/models/aria.py b/vllm/model_executor/models/aria.py
index f62d793ef..2c192c7d9 100644
--- a/vllm/model_executor/models/aria.py
+++ b/vllm/model_executor/models/aria.py
@@ -15,7 +15,9 @@ from vllm.distributed import get_tensor_model_parallel_rank
 from vllm.model_executor.layers.activation import get_act_fn
 from vllm.model_executor.layers.fused_moe import SharedFusedMoE
 from vllm.model_executor.layers.linear import ColumnParallelLinear, RowParallelLinear
+from vllm.model_executor.layers.logits_processor import LogitsProcessor
 from vllm.model_executor.layers.quantization import QuantizationConfig
+from vllm.model_executor.layers.vocab_parallel_embedding import ParallelLMHead
 from vllm.model_executor.model_loader.weight_utils import (
     default_weight_loader,
     maybe_remap_kv_scale_name,
@@ -554,6 +556,18 @@ class AriaForConditionalGeneration(nn.Module, SupportsMultiModal):
                 prefix=maybe_prefix(prefix, "language_model.model"),
             )
 
+            self.lm_head = ParallelLMHead(
+                config.text_config.vocab_size,
+                config.text_config.hidden_size,
+                quant_config=quant_config,
+                prefix=maybe_prefix(prefix, "lm_head"),
+            )
+
+            logit_scale = getattr(config, "logit_scale", 1.0)
+            self.logits_processor = LogitsProcessor(
+                config.text_config.vocab_size, scale=logit_scale
+            )
+
     def _parse_and_validate_image_input(
         self, **kwargs: object
     ) -> AriaImagePixelInputs | None:
@@ -637,7 +651,8 @@ class AriaForConditionalGeneration(nn.Module, SupportsMultiModal):
         self,
         hidden_states: torch.Tensor,
     ) -> torch.Tensor | None:
-        return self.language_model.compute_logits(hidden_states)
+        logits = self.logits_processor(self.lm_head, hidden_states)
+        return logits
 
     def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]):
         loader = AutoWeightsLoader(self)