diff --git a/src/transformers/integrations/flex_attention.py b/src/transformers/integrations/flex_attention.py
index b4d3b6fc3e01..56c35e8d1956 100644
--- a/src/transformers/integrations/flex_attention.py
+++ b/src/transformers/integrations/flex_attention.py
@@ -122,7 +122,7 @@ def make_flex_block_causal_mask(
 
     if attention_chunk_size is not None:
         # we create an arange, then we just // by chunk size to get [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]
-        document_ids = (document_ids.fill_(1).cumsum(-1) - 1) // (attention_chunk_size)
+        chunk_idxs = (document_ids.clone().fill_(1).cumsum(-1) - 1) // (attention_chunk_size)
 
     # Instead of passing a tensor mask, flex attention requires a mask_mod function
     # that determines which elements of QK^T should be included in the attention
@@ -143,6 +143,16 @@ def causal_mask_mod(batch_idx, head_idx, q_idx, kv_idx):
         final_mask = causal_mask & padding_mask & document_mask
         return final_mask
 
+    def chunk_causal_mask_mod(batch_idx, head_idx, q_idx, kv_idx):
+        """
+        Combines the chunk mask with the causal mask for chunked attention.
+        """
+        chunk_mask = chunk_idxs[batch_idx, q_idx] == chunk_idxs[batch_idx, kv_idx]
+        causal_doc_mask = causal_mask_mod(batch_idx, head_idx, q_idx, kv_idx)
+        return chunk_mask & causal_doc_mask
+
+    mask_mod_maybe_combined = causal_mask_mod if attention_chunk_size is None else chunk_causal_mask_mod
+
     if offsets is not None:
         q_offset = offsets[0]
         kv_offset = offsets[1]
@@ -150,9 +160,9 @@ def causal_mask_mod(batch_idx, head_idx, q_idx, kv_idx):
         def mask_mod(batch_idx, head_idx, q_idx, kv_idx):
             offset_q = q_idx + q_offset
             offset_kv = kv_idx + kv_offset
-            return causal_mask_mod(batch_idx, head_idx, offset_q, offset_kv)
+            return mask_mod_maybe_combined(batch_idx, head_idx, offset_q, offset_kv)
     else:
-        mask_mod = causal_mask_mod
+        mask_mod = mask_mod_maybe_combined
     return create_block_causal_mask_flex(
         mask_mod=mask_mod,
         B=batch_size,