diff --git a/langchain/text_splitter.py b/langchain/text_splitter.py
index 8a4aae2e916..0246e269e30 100644
--- a/langchain/text_splitter.py
+++ b/langchain/text_splitter.py
@@ -146,6 +146,38 @@ class CharacterTextSplitter(TextSplitter):
         return self._merge_splits(splits, self._separator)
 
 
+class TokenTextSplitter(TextSplitter):
+    """Implementation of splitting text that looks at tokens."""
+
+    def __init__(self, encoding_name: str = "gpt2", **kwargs: Any):
+        """Create a new TextSplitter."""
+        super().__init__(**kwargs)
+        try:
+            import tiktoken
+        except ImportError:
+            raise ValueError(
+                "Could not import tiktoken python package. "
+                "This is needed in order to for TokenTextSplitter. "
+                "Please it install it with `pip install tiktoken`."
+            )
+        # create a GPT-3 encoder instance
+        self._tokenizer = tiktoken.get_encoding(encoding_name)
+
+    def split_text(self, text: str) -> List[str]:
+        """Split incoming text and return chunks."""
+        splits = []
+        input_ids = self._tokenizer.encode(text)
+        start_idx = 0
+        cur_idx = min(start_idx + self._chunk_size, len(input_ids))
+        chunk_ids = input_ids[start_idx:cur_idx]
+        while start_idx < len(input_ids):
+            splits.append(self._tokenizer.decode(chunk_ids))
+            start_idx += self._chunk_size - self._chunk_overlap
+            cur_idx = min(start_idx + self._chunk_size, len(input_ids))
+            chunk_ids = input_ids[start_idx:cur_idx]
+        return splits
+
+
 class RecursiveCharacterTextSplitter(TextSplitter):
     """Implementation of splitting text that looks at characters.
 
diff --git a/tests/integration_tests/test_text_splitter.py b/tests/integration_tests/test_text_splitter.py
index 902705c7261..367899aa9ef 100644
--- a/tests/integration_tests/test_text_splitter.py
+++ b/tests/integration_tests/test_text_splitter.py
@@ -2,7 +2,7 @@
 
 import pytest
 
-from langchain.text_splitter import CharacterTextSplitter
+from langchain.text_splitter import CharacterTextSplitter, TokenTextSplitter
 
 
 def test_huggingface_type_check() -> None:
@@ -21,3 +21,21 @@ def test_huggingface_tokenizer() -> None:
     )
     output = text_splitter.split_text("foo bar")
     assert output == ["foo", "bar"]
+
+
+class TestTokenTextSplitter:
+    """Test token text splitter."""
+
+    def test_basic(self) -> None:
+        """Test no overlap."""
+        splitter = TokenTextSplitter(chunk_size=5, chunk_overlap=0)
+        output = splitter.split_text("abcdef" * 5)  # 10 token string
+        expected_output = ["abcdefabcdefabc", "defabcdefabcdef"]
+        assert output == expected_output
+
+    def test_overlap(self) -> None:
+        """Test with overlap."""
+        splitter = TokenTextSplitter(chunk_size=5, chunk_overlap=1)
+        output = splitter.split_text("abcdef" * 5)  # 10 token string
+        expected_output = ["abcdefabcdefabc", "abcdefabcdefabc", "abcdef"]
+        assert output == expected_output