diff --git a/backend/fastrtc/text_to_speech/tts.py b/backend/fastrtc/text_to_speech/tts.py
index bee94e3..ee477fd 100644
--- a/backend/fastrtc/text_to_speech/tts.py
+++ b/backend/fastrtc/text_to_speech/tts.py
@@ -14,7 +14,9 @@ class TTSOptions:
 
 
 class TTSModel(Protocol):
-    def tts(self, text: str) -> tuple[int, NDArray[np.float32]]: ...
+    def tts(
+        self, text: str, options: TTSOptions | None = None
+    ) -> tuple[int, NDArray[np.float32]]: ...
 
     async def stream_tts(
         self, text: str, options: TTSOptions | None = None
diff --git a/docs/text_to_speech_gallery.md b/docs/text_to_speech_gallery.md
new file mode 100644
index 0000000..1c4996f
--- /dev/null
+++ b/docs/text_to_speech_gallery.md
@@ -0,0 +1,128 @@
+<style>
+.tag-button {
+    cursor: pointer;
+    opacity: 0.5;
+    transition: opacity 0.2s ease;
+}
+
+.tag-button > code {
+    color: var(--supernova);
+}
+
+.tag-button.active {
+    opacity: 1;
+}
+</style>
+
+A collection of Text-to-Speech models ready to use with FastRTC. Click on the tags below to find the TTS model you're looking for!
+!!! tip "Note"
+    The model you want to use does not have to be in the gallery. This is just a collection of models with a common interface that are easy to "plug and play" into your FastRTC app. But You can use any model you want without having to do any special setup. Simply use it from your stream handler!
+
+
+<div class="tag-buttons">
+  <button class="tag-button" data-tag="cpu"><code>cpu</code></button>
+</div>
+
+<script>
+function filterCards() {
+    const activeButtons = document.querySelectorAll('.tag-button.active');
+    const selectedTags = Array.from(activeButtons).map(button => button.getAttribute('data-tag'));
+    const cards = document.querySelectorAll('.grid.cards > ul > li > p[data-tags]');
+    
+    cards.forEach(card => {
+        const cardTags = card.getAttribute('data-tags').split(',');
+        const shouldShow = selectedTags.length === 0 || selectedTags.some(tag => cardTags.includes(tag));
+        card.parentElement.style.display = shouldShow ? 'block' : 'none';
+    });
+}
+document.querySelectorAll('.tag-button').forEach(button => {
+    button.addEventListener('click', () => {
+        button.classList.toggle('active');
+        filterCards();
+    });
+});
+</script>
+
+
+<div class="grid cards" markdown>
+
+-   :speaking_head:{ .lg .middle }:eyes:{ .lg .middle } Orpheus.cpp
+{: data-tags="cpu"}
+
+    ---
+
+    Description: 
+    A llama.cpp port of [Orpheus](https://github.com/canopyai/Orpheus-TTS/tree/main) for fast lifelike speech synthesis on CPU!
+
+    Install Instructions
+    ```python
+    pip install orpheus-cpp
+    ```
+
+    <video src="https://github.com/user-attachments/assets/54dfffc9-1981-4d12-b4d1-eb68ab27e5ad" controls style="text-align: center"></video>
+
+    
+    [:octicons-code-16: Repository]([Orpheus.cpp](https://github.com/freddyaboulton/orpheus-cpp))
+
+-   :speaking_head:{ .lg .middle }:eyes:{ .lg .middle } __Your TTS Model__
+{: data-tags="pytorch"}
+
+    ---
+
+    Description
+
+    Install Instructions
+
+    Usage
+
+    [:octicons-arrow-right-24: Demo](Your demo here)
+    
+    [:octicons-code-16: Repository](Code here)
+
+</div>
+
+## How to add your own Text-to-Speech model
+
+1. Your model can be implemented in **any** framework you want but it must implement the `TTSModel` protocol.
+
+    ```python
+    class TTSModel(Protocol):
+        def tts(
+            self, text: str, options: TTSOptions | None = None
+        ) -> tuple[int, NDArray[np.float32 | np.int16]]: ...
+
+        async def stream_tts(
+            self, text: str, options: TTSOptions | None = None
+        ) -> AsyncGenerator[tuple[int, NDArray[np.float32 | np.int16]], None]: ...
+
+        def stream_tts_sync(
+            self, text: str, options: TTSOptions | None = None
+        ) -> Generator[tuple[int, NDArray[np.float32 | np.int16]], None, None]: ...
+    ```
+
+    * The `tts` methods should take in a string of the text to be spoken and an optional `TTSOptions`.
+
+    * The `audio` tuple should be of the form `(sample_rate, audio_array)` where `sample_rate` is the sample rate of the audio array and `audio_array` is a numpy array of the audio data. It can be of type `np.int16` or `np.float32`.
+
+2. Once you have your model implemented, you can use it in your handler!
+
+    ```python
+    from fastrtc import Stream, AdditionalOutputs, ReplyOnPause, get_stt_model
+    from your_model import YourModel
+
+    model = YourModel() # implement the TTSModel protocol
+    options = YourTTSOptions() # implement the TTSOptions protocol
+    stt_model = get_stt_model(model)
+
+    def echo(audio):
+        text = stt_model.tts(audio)
+        for chunk in model.stream_tts(text, options):
+            yield chunk
+
+    stream = Stream(ReplyOnPause(echo), mode="send-receive", modality="audio",
+                    additional_outputs=[gr.Textbox(label="Transcription")],
+                    additional_outputs_handler=lambda old,new:old + new)
+    stream.ui.launch()
+    ```
+
+3. Open a [PR](https://github.com/freddyaboulton/fastrtc/edit/main/docs/text_to_speech_gallery.md) to add your model to the gallery! Ideally your model package should be pip installable so other can try it out easily.
\ No newline at end of file
diff --git a/mkdocs.yml b/mkdocs.yml
index e687f4b..552fb0d 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -28,8 +28,10 @@ nav:
   - Cookbook: cookbook.md
   - Deployment: deployment.md
   - Advanced Configuration: advanced-configuration.md
-  - Speech-to-Text Gallery: speech_to_text_gallery.md
-  - Turn-taking Gallery: turn_taking_gallery.md
+  - Plugin Ecosystem:
+    - Text-to-Speech Gallery: text_to_speech_gallery.md
+    - Speech-to-Text Gallery: speech_to_text_gallery.md
+    - Turn-taking Gallery: turn_taking_gallery.md
   - Utils: utils.md
   - Frequently Asked Questions: faq.md
 extra_javascript: