diff --git a/README.md b/README.md
index 809b70b..a14c27d 100644
--- a/README.md
+++ b/README.md
@@ -158,6 +158,17 @@ nor does it try to compensate for a growing lag by skipping frames.
 Alternatively you can run `python -m moshi_mlx.local_web` to use
 the web UI, the connection is via http and will be at [localhost:8998](http://localhost:8998).
 
+
+## Gradio Demo
+
+You can launch a Gradio demo locally with the following command:
+
+```bash
+python -m moshi.client_gradio --url <moshi-server-url>
+```
+
+Prior to running the Gradio demo, please install `gradio-webrtc>=0.0.17`.
+
 ## Rust
 
 In order to run the Rust inference server, use the following command from within
diff --git a/moshi/moshi/client_gradio.py b/moshi/moshi/client_gradio.py
new file mode 100644
index 0000000..08cfdf8
--- /dev/null
+++ b/moshi/moshi/client_gradio.py
@@ -0,0 +1,163 @@
+import argparse
+from typing import Generator, Literal, cast
+
+import numpy as np
+import sphn
+from numpy.typing import NDArray
+
+try:
+    import gradio as gr
+    import websockets.sync.client
+    from gradio_webrtc import AdditionalOutputs, StreamHandler, WebRTC
+except ImportError:
+    raise ImportError("Please install gradio-webrtc>=0.0.17 to run this script.")
+
+# See https://freddyaboulton.github.io/gradio-webrtc/deployment/ for
+# instructions on how to set the rtc_configuration variable for deployment
+# on cloud platforms like Heroku, Spaces, etc.
+rtc_configuration = None
+
+
+class MoshiHandler(StreamHandler):
+    def __init__(
+        self,
+        url: str,
+        expected_layout: Literal["mono", "stereo"] = "mono",
+        output_sample_rate: int = 24000,
+        output_frame_size: int = 480,
+    ) -> None:
+        self.url = url
+        proto, without_proto = self.url.split("://", 1)
+        if proto in ["ws", "http"]:
+            proto = "ws"
+        elif proto in ["wss", "https"]:
+            proto = "wss"
+
+        self._generator = None
+        self.output_chunk_size = 1920
+        self.ws = None
+        self.ws_url = f"{proto}://{without_proto}/api/chat"
+        self.stream_reader = sphn.OpusStreamReader(output_sample_rate)
+        self.stream_writer = sphn.OpusStreamWriter(output_sample_rate)
+        self.all_output_data = None
+        super().__init__(
+            expected_layout,
+            output_sample_rate,
+            output_frame_size,
+            input_sample_rate=24000,
+        )
+
+    def receive(self, frame: tuple[int, NDArray]) -> None:
+        if not self.ws:
+            self.ws = websockets.sync.client.connect(self.ws_url)
+        _, array = frame
+        array = array.squeeze().astype(np.float32) / 32768.0
+        self.stream_writer.append_pcm(array)
+        bytes = b"\x01" + self.stream_writer.read_bytes()
+        self.ws.send(bytes)
+
+    def generator(
+        self,
+    ) -> Generator[tuple[int, NDArray] | None | AdditionalOutputs, None, None]:
+        for message in cast(websockets.sync.client.ClientConnection, self.ws):
+            if len(message) == 0:
+                yield None
+            kind = message[0]
+            if kind == 1:
+                payload = message[1:]
+                self.stream_reader.append_bytes(payload)
+                pcm = self.stream_reader.read_pcm()
+                if self.all_output_data is None:
+                    self.all_output_data = pcm
+                else:
+                    self.all_output_data = np.concatenate((self.all_output_data, pcm))
+                while self.all_output_data.shape[-1] >= self.output_chunk_size:
+                    yield (
+                        self.output_sample_rate,
+                        self.all_output_data[: self.output_chunk_size].reshape(1, -1),
+                    )
+                    self.all_output_data = np.array(
+                        self.all_output_data[self.output_chunk_size :]
+                    )
+            elif kind == 2:
+                payload = cast(bytes, message[1:])
+                yield AdditionalOutputs(payload.decode())
+
+    def emit(self) -> tuple[int, NDArray] | AdditionalOutputs | None:
+        if not self.ws:
+            return
+        if not self._generator:
+            self._generator = self.generator()
+        try:
+            return next(self._generator)
+        except StopIteration:
+            self.reset()
+
+    def reset(self) -> None:
+        self._generator = None
+        self.all_output_data = None
+
+    def copy(self) -> StreamHandler:
+        return MoshiHandler(
+            self.url,
+            self.expected_layout,  # type: ignore
+            self.output_sample_rate,
+            self.output_frame_size,
+        )
+
+    def shutdown(self) -> None:
+        if self.ws:
+            self.ws.close()
+
+
+def main():
+    parser = argparse.ArgumentParser("client_gradio")
+    parser.add_argument("--url", type=str, help="URL to moshi server.")
+    args = parser.parse_args()
+
+    with gr.Blocks() as demo:
+        gr.HTML(
+            """
+        <div style='text-align: center'>
+            <h1>
+                Talk To Moshi (Powered by WebRTC ⚡️)
+            </h1>
+            <p>
+                Each conversation is limited to 90 seconds. Once the time limit is up you can rejoin the conversation.
+            </p>
+        </div>
+        """
+        )
+        chatbot = gr.Chatbot(type="messages", value=[])
+        webrtc = WebRTC(
+            label="Conversation",
+            modality="audio",
+            mode="send-receive",
+            rtc_configuration=rtc_configuration,
+        )
+        webrtc.stream(
+            MoshiHandler(args.url),
+            inputs=[webrtc, chatbot],
+            outputs=[webrtc],
+            time_limit=90,
+        )
+
+        def add_text(chat_history, response):
+            if len(chat_history) == 0:
+                chat_history.append({"role": "assistant", "content": ""})
+            chat_history[-1]["content"] += response
+            return chat_history
+
+        webrtc.on_additional_outputs(
+            add_text,
+            inputs=[chatbot],
+            outputs=chatbot,
+            queue=False,
+            show_progress="hidden",
+        )
+
+        demo.launch()
+
+
+if __name__ == "__main__":
+    main()