diff --git a/vllm_mlx/server.py b/vllm_mlx/server.py
index 19c8a3f7..4bd9c426 100644
--- a/vllm_mlx/server.py
+++ b/vllm_mlx/server.py
@@ -47,7 +47,7 @@
 from contextlib import asynccontextmanager
 from typing import AsyncIterator, Optional
 
-from fastapi import FastAPI, HTTPException
+from fastapi import FastAPI, HTTPException, UploadFile
 from fastapi.responses import StreamingResponse
 
 # Import from new modular API
@@ -173,7 +173,10 @@ def load_model(
         logger.info(f"Loading model with SimpleEngine: {model_name}")
         _engine = SimpleEngine(model_name=model_name)
         # Start SimpleEngine synchronously (no background loop)
-        asyncio.get_event_loop().run_until_complete(_engine.start())
+        # Use new_event_loop() for Python 3.10+ compatibility (get_event_loop() is deprecated)
+        loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(loop)
+        loop.run_until_complete(_engine.start())
         model_type = "MLLM" if _engine.is_mllm else "LLM"
         logger.info(f"{model_type} model loaded (simple mode): {model_name}")
 
@@ -278,6 +281,152 @@ async def execute_mcp_tool(request: MCPExecuteRequest) -> MCPExecuteResponse:
     )
 
 
+# =============================================================================
+# Audio Endpoints
+# =============================================================================
+
+# Global audio engines (lazy loaded)
+_stt_engine = None
+_tts_engine = None
+
+
+@app.post("/v1/audio/transcriptions")
+async def create_transcription(
+    file: UploadFile,
+    model: str = "whisper-large-v3",
+    language: Optional[str] = None,
+    response_format: str = "json",
+):
+    """
+    Transcribe audio to text (OpenAI Whisper API compatible).
+
+    Supported models:
+    - whisper-large-v3 (multilingual, best quality)
+    - whisper-large-v3-turbo (faster)
+    - whisper-medium, whisper-small (lighter)
+    - parakeet-tdt-0.6b-v2 (English, fastest)
+    """
+    global _stt_engine
+    import tempfile
+    import os
+
+    try:
+        from .audio.stt import STTEngine
+
+        # Map model aliases to full names
+        model_map = {
+            "whisper-large-v3": "mlx-community/whisper-large-v3-mlx",
+            "whisper-large-v3-turbo": "mlx-community/whisper-large-v3-turbo",
+            "whisper-medium": "mlx-community/whisper-medium-mlx",
+            "whisper-small": "mlx-community/whisper-small-mlx",
+            "parakeet": "mlx-community/parakeet-tdt-0.6b-v2",
+            "parakeet-v3": "mlx-community/parakeet-tdt-0.6b-v3",
+        }
+        model_name = model_map.get(model, model)
+
+        # Load engine if needed
+        if _stt_engine is None or _stt_engine.model_name != model_name:
+            _stt_engine = STTEngine(model_name)
+            _stt_engine.load()
+
+        # Save uploaded file temporarily
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp:
+            content = await file.read()
+            tmp.write(content)
+            tmp_path = tmp.name
+
+        try:
+            result = _stt_engine.transcribe(tmp_path, language=language)
+        finally:
+            os.unlink(tmp_path)
+
+        if response_format == "text":
+            return result.text
+
+        return {
+            "text": result.text,
+            "language": result.language,
+            "duration": result.duration,
+        }
+
+    except ImportError:
+        raise HTTPException(
+            status_code=503,
+            detail="mlx-audio not installed. Install with: pip install mlx-audio"
+        )
+    except Exception as e:
+        logger.error(f"Transcription failed: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/v1/audio/speech")
+async def create_speech(
+    model: str = "kokoro",
+    input: str = "",
+    voice: str = "af_heart",
+    speed: float = 1.0,
+    response_format: str = "wav",
+):
+    """
+    Generate speech from text (OpenAI TTS API compatible).
+
+    Supported models:
+    - kokoro (fast, lightweight)
+    - chatterbox (multilingual, expressive)
+    - vibevoice (realtime)
+    - voxcpm (Chinese/English)
+    """
+    global _tts_engine
+    from fastapi.responses import Response
+
+    try:
+        from .audio.tts import TTSEngine
+
+        # Map model aliases to full names
+        model_map = {
+            "kokoro": "mlx-community/Kokoro-82M-bf16",
+            "kokoro-4bit": "mlx-community/Kokoro-82M-4bit",
+            "chatterbox": "mlx-community/chatterbox-turbo-fp16",
+            "chatterbox-4bit": "mlx-community/chatterbox-turbo-4bit",
+            "vibevoice": "mlx-community/VibeVoice-Realtime-0.5B-4bit",
+            "voxcpm": "mlx-community/VoxCPM1.5",
+        }
+        model_name = model_map.get(model, model)
+
+        # Load engine if needed
+        if _tts_engine is None or _tts_engine.model_name != model_name:
+            _tts_engine = TTSEngine(model_name)
+            _tts_engine.load()
+
+        audio = _tts_engine.generate(input, voice=voice, speed=speed)
+        audio_bytes = _tts_engine.to_bytes(audio, format=response_format)
+
+        content_type = "audio/wav" if response_format == "wav" else f"audio/{response_format}"
+        return Response(content=audio_bytes, media_type=content_type)
+
+    except ImportError:
+        raise HTTPException(
+            status_code=503,
+            detail="mlx-audio not installed. Install with: pip install mlx-audio"
+        )
+    except Exception as e:
+        logger.error(f"TTS generation failed: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/v1/audio/voices")
+async def list_voices(model: str = "kokoro"):
+    """List available voices for a TTS model."""
+    from .audio.tts import KOKORO_VOICES, CHATTERBOX_VOICES
+
+    if "kokoro" in model.lower():
+        return {"voices": KOKORO_VOICES}
+    elif "chatterbox" in model.lower():
+        return {"voices": CHATTERBOX_VOICES}
+    else:
+        return {"voices": ["default"]}
+
+
 # =============================================================================
 # Completion Endpoints
 # =============================================================================