diff --git a/vllm/model_executor/models/llama.py b/vllm/model_executor/models/llama.py
index 93ab499e64a2..7d8c950cb2a9 100644
--- a/vllm/model_executor/models/llama.py
+++ b/vllm/model_executor/models/llama.py
@@ -85,6 +85,7 @@ class LlamaAttention(nn.Module):
         hidden_size: int,
         num_heads: int,
         num_kv_heads: int,
+        rope_theta: float = 10000,
     ):
         super().__init__()
         self.hidden_size = hidden_size
@@ -99,6 +100,7 @@ class LlamaAttention(nn.Module):
         self.q_size = self.num_heads * self.head_dim
         self.kv_size = self.num_kv_heads * self.head_dim
         self.scaling = self.head_dim**-0.5
+        self.rope_theta = rope_theta
 
         self.qkv_proj = ColumnParallelLinear(
             hidden_size,
@@ -118,6 +120,7 @@ class LlamaAttention(nn.Module):
         self.attn = PagedAttentionWithRoPE(self.num_heads,
                                            self.head_dim,
                                            self.scaling,
+                                           base=self.rope_theta,
                                            rotary_dim=self.head_dim,
                                            num_kv_heads=self.num_kv_heads)
 
@@ -143,10 +146,13 @@ class LlamaDecoderLayer(nn.Module):
     def __init__(self, config: LlamaConfig):
         super().__init__()
         self.hidden_size = config.hidden_size
+        # Requires transformers > 4.32.0
+        rope_theta = getattr(config, "rope_theta", 10000)
         self.self_attn = LlamaAttention(
             hidden_size=self.hidden_size,
             num_heads=config.num_attention_heads,
             num_kv_heads=config.num_key_value_heads,
+            rope_theta=rope_theta,
         )
         self.mlp = LlamaMLP(
             hidden_size=self.hidden_size,