diff --git a/tests/integration/vector_io/test_openai_vector_stores.py b/tests/integration/vector_io/test_openai_vector_stores.py
index 0a5409ad9..1c9ef92b6 100644
--- a/tests/integration/vector_io/test_openai_vector_stores.py
+++ b/tests/integration/vector_io/test_openai_vector_stores.py
@@ -52,7 +52,6 @@ def skip_if_provider_doesnt_support_openai_vector_stores_search(client_with_mode
         ],
         "keyword": [
             "inline::sqlite-vec",
-            "remote::chromadb",
         ],
         "hybrid": [
             "inline::sqlite-vec",
diff --git a/tests/unit/providers/vector_io/remote/test_chroma.py b/tests/unit/providers/vector_io/remote/test_chroma.py
new file mode 100644
index 000000000..ea9134f99
--- /dev/null
+++ b/tests/unit/providers/vector_io/remote/test_chroma.py
@@ -0,0 +1,124 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import json
+from unittest.mock import MagicMock, patch
+
+import numpy as np
+import pytest
+
+from llama_stack.apis.vector_io import QueryChunksResponse
+
+# Mock the entire chromadb module
+chromadb_mock = MagicMock()
+chromadb_mock.AsyncHttpClient = MagicMock
+chromadb_mock.PersistentClient = MagicMock
+
+# Apply the mock before importing ChromaIndex
+with patch.dict("sys.modules", {"chromadb": chromadb_mock}):
+    from llama_stack.providers.remote.vector_io.chroma.chroma import ChromaIndex
+
+# This test is a unit test for the ChromaVectorIOAdapter class. This should only contain
+# tests which are specific to this class. More general (API-level) tests should be placed in
+# tests/integration/vector_io/
+#
+# How to run this test:
+#
+# pytest tests/unit/providers/vector_io/test_chroma.py \
+# -v -s --tb=short --disable-warnings --asyncio-mode=auto
+
+CHROMA_PROVIDER = "chromadb"
+
+
+@pytest.fixture
+async def mock_chroma_collection() -> MagicMock:
+    """Create a mock Chroma collection with common method behaviors."""
+    collection = MagicMock()
+    collection.name = "test_collection"
+
+    # Mock add operation
+    collection.add.return_value = None
+
+    # Mock query operation for vector search
+    collection.query.return_value = {
+        "distances": [[0.1, 0.2]],
+        "documents": [
+            [
+                json.dumps({"content": "mock chunk 1", "metadata": {"document_id": "doc1"}}),
+                json.dumps({"content": "mock chunk 2", "metadata": {"document_id": "doc2"}}),
+            ]
+        ],
+    }
+
+    # Mock delete operation
+    collection.delete.return_value = None
+
+    return collection
+
+
+@pytest.fixture
+async def mock_chroma_client(mock_chroma_collection):
+    """Create a mock Chroma client with common method behaviors."""
+    client = MagicMock()
+
+    # Mock collection operations
+    client.get_or_create_collection.return_value = mock_chroma_collection
+    client.get_collection.return_value = mock_chroma_collection
+    client.delete_collection.return_value = None
+
+    return client
+
+
+@pytest.fixture
+async def chroma_index(mock_chroma_client, mock_chroma_collection):
+    """Create a ChromaIndex with mocked client and collection."""
+    index = ChromaIndex(client=mock_chroma_client, collection=mock_chroma_collection)
+    yield index
+    # No real cleanup needed since we're using mocks
+
+
+async def test_add_chunks(chroma_index, sample_chunks, sample_embeddings, mock_chroma_collection):
+    await chroma_index.add_chunks(sample_chunks, sample_embeddings)
+
+    # Verify data was inserted
+    mock_chroma_collection.add.assert_called_once()
+
+    # Verify the add call had the right number of chunks
+    add_call = mock_chroma_collection.add.call_args
+    assert len(add_call[1]["documents"]) == len(sample_chunks)
+
+
+async def test_query_chunks_vector(
+    chroma_index, sample_chunks, sample_embeddings, embedding_dimension, mock_chroma_collection
+):
+    # Setup: Add chunks first
+    await chroma_index.add_chunks(sample_chunks, sample_embeddings)
+
+    # Test vector search
+    query_embedding = np.random.rand(embedding_dimension).astype(np.float32)
+    response = await chroma_index.query_vector(query_embedding, k=2, score_threshold=0.0)
+
+    assert isinstance(response, QueryChunksResponse)
+    assert len(response.chunks) == 2
+    mock_chroma_collection.query.assert_called_once()
+
+
+async def test_query_chunks_keyword_search(chroma_index, sample_chunks, sample_embeddings, mock_chroma_collection):
+    await chroma_index.add_chunks(sample_chunks, sample_embeddings)
+
+    # Test keyword search
+    query_string = "Sentence 5"
+    response = await chroma_index.query_keyword(query_string=query_string, k=2, score_threshold=0.0)
+
+    assert isinstance(response, QueryChunksResponse)
+    assert len(response.chunks) == 2
+
+
+async def test_delete_collection(chroma_index, mock_chroma_client):
+    # Test collection deletion
+    await chroma_index.delete()
+
+    mock_chroma_client.delete_collection.assert_called_once_with(chroma_index.collection.name)