diff --git a/docs/my-website/docs/providers/vertex.md b/docs/my-website/docs/providers/vertex.md
index 697aa0701..582636630 100644
--- a/docs/my-website/docs/providers/vertex.md
+++ b/docs/my-website/docs/providers/vertex.md
@@ -1768,7 +1768,7 @@ LiteLLM supports calling [Vertex AI Text to Speech API](https://console.cloud.go
 
 
 
-Usage
+### Usage - Basic
 
 <Tabs>
 <TabItem value="sdk" label="SDK">
@@ -1841,6 +1841,150 @@ print("response from proxy", response)
 </Tabs>
 
 
+### Usage - `ssml` as input
+
+Pass your `ssml` as input to the `input` param, if it contains `<speak>`, it will be automatically detected and passed as `ssml` to the Vertex AI API
+
+If you need to force your `input` to be passed as `ssml`, set `use_ssml=True`
+
+<Tabs>
+<TabItem value="sdk" label="SDK">
+
+Vertex AI does not support passing a `model` param - so passing `model=vertex_ai/` is the only required param
+
+
+```python
+speech_file_path = Path(__file__).parent / "speech_vertex.mp3"
+
+
+ssml = """
+<speak>
+    <p>Hello, world!</p>
+    <p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
+</speak>
+"""
+
+response = litellm.speech(
+    input=ssml,
+    model="vertex_ai/test",
+    voice={
+        "languageCode": "en-UK",
+        "name": "en-UK-Studio-O",
+    },
+    audioConfig={
+        "audioEncoding": "LINEAR22",
+        "speakingRate": "10",
+    },
+)
+response.stream_to_file(speech_file_path)
+```
+
+</TabItem>
+
+<TabItem value="proxy" label="LiteLLM PROXY (Unified Endpoint)">
+
+```python
+import openai
+
+client = openai.OpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000")
+
+ssml = """
+<speak>
+    <p>Hello, world!</p>
+    <p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
+</speak>
+"""
+
+# see supported values for "voice" on vertex here: 
+# https://console.cloud.google.com/vertex-ai/generative/speech/text-to-speech
+response = client.audio.speech.create(
+    model = "vertex-tts",
+    input=ssml,
+    voice={'languageCode': 'en-US', 'name': 'en-US-Studio-O'},
+)
+print("response from proxy", response)
+```
+
+</TabItem>
+</Tabs>
+
+
+### Forcing SSML Usage
+
+You can force the use of SSML by setting the `use_ssml` parameter to `True`. This is useful when you want to ensure that your input is treated as SSML, even if it doesn't contain the `<speak>` tags.
+
+Here are examples of how to force SSML usage:
+
+
+<Tabs>
+<TabItem value="sdk" label="SDK">
+
+Vertex AI does not support passing a `model` param - so passing `model=vertex_ai/` is the only required param
+
+
+```python
+speech_file_path = Path(__file__).parent / "speech_vertex.mp3"
+
+
+ssml = """
+<speak>
+    <p>Hello, world!</p>
+    <p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
+</speak>
+"""
+
+response = litellm.speech(
+    input=ssml,
+    use_ssml=True,
+    model="vertex_ai/test",
+    voice={
+        "languageCode": "en-UK",
+        "name": "en-UK-Studio-O",
+    },
+    audioConfig={
+        "audioEncoding": "LINEAR22",
+        "speakingRate": "10",
+    },
+)
+response.stream_to_file(speech_file_path)
+```
+
+</TabItem>
+
+<TabItem value="proxy" label="LiteLLM PROXY (Unified Endpoint)">
+
+```python
+import openai
+
+client = openai.OpenAI(api_key="sk-1234", base_url="http://0.0.0.0:4000")
+
+ssml = """
+<speak>
+    <p>Hello, world!</p>
+    <p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
+</speak>
+"""
+
+# see supported values for "voice" on vertex here: 
+# https://console.cloud.google.com/vertex-ai/generative/speech/text-to-speech
+response = client.audio.speech.create(
+    model = "vertex-tts",
+    input=ssml, # pass as None since OpenAI SDK requires this param
+    voice={'languageCode': 'en-US', 'name': 'en-US-Studio-O'},
+    extra_body={"use_ssml": True},
+)
+print("response from proxy", response)
+```
+
+</TabItem>
+</Tabs>
+
+
+
+
+
+
+
 ## Extra
 
 ### Using `GOOGLE_APPLICATION_CREDENTIALS`
diff --git a/litellm/llms/text_to_speech/vertex_ai.py b/litellm/llms/text_to_speech/vertex_ai.py
index b9fca5325..39c5ddfd4 100644
--- a/litellm/llms/text_to_speech/vertex_ai.py
+++ b/litellm/llms/text_to_speech/vertex_ai.py
@@ -19,7 +19,8 @@ from litellm.llms.vertex_ai_and_google_ai_studio.vertex_and_google_ai_studio_gem
 
 
 class VertexInput(TypedDict, total=False):
-    text: str
+    text: Optional[str]
+    ssml: Optional[str]
 
 
 class VertexVoice(TypedDict, total=False):
@@ -86,10 +87,13 @@ class VertexTextToSpeechAPI(VertexLLM):
 
         ####### Build the request ################
         # API Ref: https://cloud.google.com/text-to-speech/docs/reference/rest/v1/text/synthesize
-        vertex_input = VertexInput(text=input)
-        # required param
-        optional_params = optional_params or {}
         kwargs = kwargs or {}
+        optional_params = optional_params or {}
+
+        vertex_input = VertexInput(text=input)
+        validate_vertex_input(vertex_input, kwargs, optional_params)
+
+        # required param
         if voice is not None:
             vertex_voice = VertexVoice(**voice)
         elif "voice" in kwargs:
@@ -203,3 +207,34 @@ class VertexTextToSpeechAPI(VertexLLM):
         # Initialize the HttpxBinaryResponseContent instance
         http_binary_response = HttpxBinaryResponseContent(response)
         return http_binary_response
+
+
+def validate_vertex_input(
+    input_data: VertexInput, kwargs: dict, optional_params: dict
+) -> None:
+    # Remove None values
+    if input_data.get("text") is None:
+        input_data.pop("text", None)
+    if input_data.get("ssml") is None:
+        input_data.pop("ssml", None)
+
+    # Check if use_ssml is set
+    use_ssml = kwargs.get("use_ssml", optional_params.get("use_ssml", False))
+
+    if use_ssml:
+        if "text" in input_data:
+            input_data["ssml"] = input_data.pop("text")
+        elif "ssml" not in input_data:
+            raise ValueError("SSML input is required when use_ssml is True.")
+    else:
+        # LiteLLM will auto-detect if text is in ssml format
+        # check if "text" is an ssml - in this case we should pass it as ssml instead of text
+        if input_data:
+            _text = input_data.get("text", None) or ""
+            if "<speak>" in _text:
+                input_data["ssml"] = input_data.pop("text")
+
+    if not input_data:
+        raise ValueError("Either 'text' or 'ssml' must be provided.")
+    if "text" in input_data and "ssml" in input_data:
+        raise ValueError("Only one of 'text' or 'ssml' should be provided, not both.")
diff --git a/litellm/tests/test_audio_speech.py b/litellm/tests/test_audio_speech.py
index 5de996fa1..2c710d37e 100644
--- a/litellm/tests/test_audio_speech.py
+++ b/litellm/tests/test_audio_speech.py
@@ -243,3 +243,61 @@ async def test_speech_litellm_vertex_async_with_voice():
             "voice": {"languageCode": "en-UK", "name": "en-UK-Studio-O"},
             "audioConfig": {"audioEncoding": "LINEAR22", "speakingRate": "10"},
         }
+
+
+@pytest.mark.asyncio
+async def test_speech_litellm_vertex_async_with_voice_ssml():
+    # Mock the response
+    mock_response = AsyncMock()
+
+    def return_val():
+        return {
+            "audioContent": "dGVzdCByZXNwb25zZQ==",
+        }
+
+    mock_response.json = return_val
+    mock_response.status_code = 200
+
+    ssml = """
+    <speak>
+        <p>Hello, world!</p>
+        <p>This is a test of the <break strength="medium" /> text-to-speech API.</p>
+    </speak>
+    """
+
+    # Set up the mock for asynchronous calls
+    with patch(
+        "litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
+        new_callable=AsyncMock,
+    ) as mock_async_post:
+        mock_async_post.return_value = mock_response
+        model = "vertex_ai/test"
+
+        response = await litellm.aspeech(
+            input=ssml,
+            model=model,
+            voice={
+                "languageCode": "en-UK",
+                "name": "en-UK-Studio-O",
+            },
+            audioConfig={
+                "audioEncoding": "LINEAR22",
+                "speakingRate": "10",
+            },
+        )
+
+        # Assert asynchronous call
+        mock_async_post.assert_called_once()
+        _, kwargs = mock_async_post.call_args
+        print("call args", kwargs)
+
+        assert kwargs["url"] == "https://texttospeech.googleapis.com/v1/text:synthesize"
+
+        assert "x-goog-user-project" in kwargs["headers"]
+        assert kwargs["headers"]["Authorization"] is not None
+
+        assert kwargs["json"] == {
+            "input": {"ssml": ssml},
+            "voice": {"languageCode": "en-UK", "name": "en-UK-Studio-O"},
+            "audioConfig": {"audioEncoding": "LINEAR22", "speakingRate": "10"},
+        }