diff --git a/openviking/models/embedder/openai_embedders.py b/openviking/models/embedder/openai_embedders.py
index a0a76e9e8f..909061bec3 100644
--- a/openviking/models/embedder/openai_embedders.py
+++ b/openviking/models/embedder/openai_embedders.py
@@ -2,7 +2,7 @@
 # SPDX-License-Identifier: AGPL-3.0
 """OpenAI Embedder Implementation"""
 
-from typing import Any, Dict, List, Literal, Optional
+from typing import Any, Dict, List, Literal, Optional, cast
 
 import httpx
 import openai
@@ -22,6 +22,7 @@
 from openviking.models.vlm.registry import DEFAULT_AZURE_API_VERSION
 from openviking.telemetry import get_current_telemetry
 from openviking.utils.async_client_cache import LoopScopedAsyncClientCache
+from openviking.utils.embedding_input import truncate_embedding_input
 from openviking_cli.utils import get_logger
 
 logger = get_logger(__name__)
@@ -322,7 +323,10 @@ def supports_multimodal(self) -> bool:
 
     def _prepare_embedding_input(self, text: EmbeddingInput | List[str]) -> EmbeddingInput | List[str]:
         if isinstance(text, list) and all(isinstance(item, str) for item in text):
-            return text
+            if self.max_input_tokens is None:
+                return text
+            text = cast(List[str], text)
+            return [truncate_embedding_input(item, self.max_input_tokens) for item in text]
         return self.prepare_embedding_input(text)
 
     def _build_kwargs(
diff --git a/tests/unit/test_openai_embedder.py b/tests/unit/test_openai_embedder.py
index 5ca3090ef0..e812ce0f5f 100644
--- a/tests/unit/test_openai_embedder.py
+++ b/tests/unit/test_openai_embedder.py
@@ -87,7 +87,7 @@ def test_default_input_type_embed_downgrades_multimodal_parts(self, mock_openai_
 
     @patch("openviking.models.embedder.openai_embedders.openai.OpenAI")
     def test_embed_preserves_openai_batch_text_input(self, mock_openai_class):
-        """OpenAI batch text input should keep the historical list[str] passthrough."""
+        """OpenAI batches keep item boundaries and truncate each oversized item."""
         mock_client = MagicMock()
         mock_openai_class.return_value = mock_client
 
@@ -101,13 +101,13 @@ def test_embed_preserves_openai_batch_text_input(self, mock_openai_class):
         embedder = OpenAIDenseEmbedder(
             model_name="text-embedding-3-small",
             api_key="test-api-key",
-            dimension=1536,
+            config={"max_input_tokens": 1},
         )
 
-        embedder.embed(["first text", "second text"])
+        embedder.embed(["first text", "x"])
 
         call_kwargs = mock_client.embeddings.create.call_args[1]
-        assert call_kwargs["input"] == ["first text", "second text"]
+        assert call_kwargs["input"] == ["firs\n...(truncated for embedding)", "x"]
 
     @patch("openviking.models.embedder.openai_embedders.openai.OpenAI")
     def test_multimodal_input_type_passes_content_parts(self, mock_openai_class):