diff --git a/src/liquid_audio/demo/chat.py b/src/liquid_audio/demo/chat.py
index b186529..2b3db20 100644
--- a/src/liquid_audio/demo/chat.py
+++ b/src/liquid_audio/demo/chat.py
@@ -8,7 +8,7 @@
 
 from liquid_audio import ChatState, LFMModality
 
-from .model import lfm2_audio, mimi, proc
+from .model import device, lfm2_audio, mimi, proc
 
 
 def chat_producer(
@@ -91,7 +91,7 @@ def chat_response(audio: tuple[int, np.ndarray], _id: str, chat: ChatState, temp
     chat.append(
         text=torch.stack(out_text, 1),
         audio_out=torch.stack(out_audio, 1),
-        modality_flag=torch.tensor(out_modality, device="cuda"),
+        modality_flag=torch.tensor(out_modality, device=device),
     )
 
     chat.end_turn()
@@ -122,7 +122,7 @@ def clear():
     webrtc.stream(
         ReplyOnPause(
             chat_response,  # type: ignore[arg-type]
-            input_sample_rate=24_000,
+            input_sample_rate=48_000,
             output_sample_rate=24_000,
             can_interrupt=False,
         ),
diff --git a/src/liquid_audio/demo/model.py b/src/liquid_audio/demo/model.py
index 8b27506..739b4d4 100644
--- a/src/liquid_audio/demo/model.py
+++ b/src/liquid_audio/demo/model.py
@@ -8,19 +8,26 @@
 
 logger = logging.getLogger(__name__)
 
-__all__ = ["lfm2_audio", "mimi", "proc"]
+__all__ = ["lfm2_audio", "mimi", "proc", "device"]
 
 HF_DIR = "LiquidAI/LFM2.5-Audio-1.5B"
 
+if torch.cuda.is_available():
+    device = "cuda"
+elif torch.backends.mps.is_available():
+    device = "mps"
+else:
+    device = "cpu"
+
 logging.info("Loading processor")
-proc = LFM2AudioProcessor.from_pretrained(HF_DIR).eval()
+proc = LFM2AudioProcessor.from_pretrained(HF_DIR, device=device).eval()
 logging.info("Loading model")
-lfm2_audio = LFM2AudioModel.from_pretrained(HF_DIR).eval()
+lfm2_audio = LFM2AudioModel.from_pretrained(HF_DIR, device=device).eval()
 logging.info("Loading tokenizer")
 mimi = proc.mimi.eval()
 
 logging.info("Warmup tokenizer")
 with mimi.streaming(1), torch.no_grad():
     for _ in range(5):
-        x = torch.randint(2048, (1, 8, 1), device="cuda")
+        x = torch.randint(2048, (1, 8, 1), device=device)
         mimi.decode(x)
diff --git a/src/liquid_audio/processor.py b/src/liquid_audio/processor.py
index 7c60fed..c602eb2 100644
--- a/src/liquid_audio/processor.py
+++ b/src/liquid_audio/processor.py
@@ -111,7 +111,9 @@ def mimi(self) -> MimiModel:
             from safetensors.torch import load_file
 
             mimi_model = moshi.models.loaders.get_mimi(None, device=self.device)
-            mimi_weights = load_file(self.mimi_weights_path, device=str(self.device))
+            # safetensors only supports cpu/cuda as load targets
+            load_device = str(self.device) if self.device.type in ("cpu", "cuda") else "cpu"
+            mimi_weights = load_file(self.mimi_weights_path, device=load_device)
             mimi_model.load_state_dict(mimi_weights, strict=True)
 
             self._mimi = mimi_model
@@ -148,7 +150,7 @@ def rename_layer(
             assert isinstance(detok_config.layer_types, list)
             detok_config.layer_types = [rename_layer(layer) for layer in detok_config.layer_types]  # type: ignore[arg-type]
 
-            detok = LFM2AudioDetokenizer(detok_config).eval().cuda()
+            detok = LFM2AudioDetokenizer(detok_config).eval().to(self.device)
 
             detok_weights_path = Path(self.detokenizer_path) / "model.safetensors"
             from safetensors.torch import load_file