diff --git a/mem0/embeddings/openai.py b/mem0/embeddings/openai.py
index 302809408..42ff4b374 100644
--- a/mem0/embeddings/openai.py
+++ b/mem0/embeddings/openai.py
@@ -13,6 +13,9 @@ class OpenAIEmbedding(EmbeddingBase):
         super().__init__(config)
 
         self.config.model = self.config.model or "text-embedding-3-small"
+        # Only pass `dimensions` to the API when the user set embedding_dims; non-matryoshka
+        # OpenAI-compatible backends (vLLM, Voyage, etc.) reject the parameter
+        self._pass_dimensions_to_api = self.config.embedding_dims is not None
         self.config.embedding_dims = self.config.embedding_dims or 1536
 
         api_key = self.config.api_key or os.getenv("OPENAI_API_KEY")
@@ -42,13 +45,11 @@ class OpenAIEmbedding(EmbeddingBase):
             list: The embedding vector.
         """
         text = text.replace("\n", " ")
-        return (
-            self.client.embeddings.create(
-                input=[text],
-                model=self.config.model,
-                dimensions=self.config.embedding_dims,
-                encoding_format="float",
-            )
-            .data[0]
-            .embedding
-        )
+        kwargs = {
+            "input": [text],
+            "model": self.config.model,
+            "encoding_format": "float",
+        }
+        if self._pass_dimensions_to_api:
+            kwargs["dimensions"] = self.config.embedding_dims
+        return self.client.embeddings.create(**kwargs).data[0].embedding
diff --git a/tests/embeddings/test_openai_embeddings.py b/tests/embeddings/test_openai_embeddings.py
index 722041fd6..4291d1a91 100644
--- a/tests/embeddings/test_openai_embeddings.py
+++ b/tests/embeddings/test_openai_embeddings.py
@@ -24,7 +24,7 @@ def test_embed_default_model(mock_openai_client):
     result = embedder.embed("Hello world")
 
     mock_openai_client.embeddings.create.assert_called_once_with(
-        input=["Hello world"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
+        input=["Hello world"], model="text-embedding-3-small", encoding_format="float"
     )
     assert result == [0.1, 0.2, 0.3]
 
@@ -54,7 +54,7 @@ def test_embed_removes_newlines(mock_openai_client):
     result = embedder.embed("Hello\nworld")
 
     mock_openai_client.embeddings.create.assert_called_once_with(
-        input=["Hello world"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
+        input=["Hello world"], model="text-embedding-3-small", encoding_format="float"
     )
     assert result == [0.7, 0.8, 0.9]
 
@@ -69,7 +69,7 @@ def test_embed_without_api_key_env_var(mock_openai_client):
     result = embedder.embed("Testing API key")
 
     mock_openai_client.embeddings.create.assert_called_once_with(
-        input=["Testing API key"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
+        input=["Testing API key"], model="text-embedding-3-small", encoding_format="float"
     )
     assert result == [1.0, 1.1, 1.2]
 
@@ -85,7 +85,7 @@ def test_embed_uses_environment_api_key(mock_openai_client, monkeypatch):
     result = embedder.embed("Environment key test")
 
     mock_openai_client.embeddings.create.assert_called_once_with(
-        input=["Environment key test"], model="text-embedding-3-small", dimensions=1536, encoding_format="float"
+        input=["Environment key test"], model="text-embedding-3-small", encoding_format="float"
     )
     assert result == [1.3, 1.4, 1.5]
 
@@ -107,3 +107,18 @@ def test_embed_passes_encoding_format_float(mock_openai_client):
 
     call_kwargs = mock_openai_client.embeddings.create.call_args
     assert call_kwargs.kwargs.get("encoding_format") == "float" or call_kwargs[1].get("encoding_format") == "float"
+
+
+def test_embed_passes_dimensions_only_when_explicit(mock_openai_client):
+    """Matryoshka / truncated embeddings: dimensions sent only if user sets embedding_dims (#4153)."""
+    config = BaseEmbedderConfig(embedding_dims=256)
+    embedder = OpenAIEmbedding(config)
+    mock_response = Mock()
+    mock_response.data = [Mock(embedding=[0.1] * 256)]
+    mock_openai_client.embeddings.create.return_value = mock_response
+
+    embedder.embed("truncate me")
+
+    mock_openai_client.embeddings.create.assert_called_once_with(
+        input=["truncate me"], model="text-embedding-3-small", dimensions=256, encoding_format="float"
+    )