diff --git a/CLAUDE.md b/CLAUDE.md
index 81bcdc3..7e101be 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -107,8 +107,8 @@ When adding features, update ALL relevant docs:
 # 1. Clean everything
 make clean
 
-# 2. Deploy (syncs files, creates env, builds container)
-make deploy
+# 2. Deploy (commit, push, pull on server, rebuild container)
+git push && tmux send-keys -t 0:1 'cd ~/git/uncloseai-speech && git pull && sudo docker-compose up --build -d' Enter
 
 # 3. Download voices (Piper + XTTS samples)
 make voices
@@ -125,7 +125,7 @@ make test-xtts
 3. Implement engine wrapper in `speech.py` or `src/engines/`
 4. Add test target (e.g., `test-silero`)
 5. Update `make voices` to include it
-6. Test full cycle: `make clean && make deploy && make voices`
+6. Test full cycle: commit, push, pull on server, rebuild, test
 
 ### Debugging Issues
 
@@ -195,30 +195,31 @@ See `docs/MODELS.md` for complete roadmap and detailed model documentation.
 
 ## Production Deployment
 
-**Production Server:** `ai.foxhop.net`
-- **URL:** https://ai.foxhop.net (port 8000 internal)
+**Production Server:** `3090-ai.foxhop.net`
+- **URL:** https://speech.ai.unturf.com (proxied via ai.foxhop.net)
 - **Repo Location:** `/home/fox/git/uncloseai-speech`
-- **Container:** `uncloseai-speech-server-1` (image: `uncloseai-speech:local`)
-- **tmux access:** `tmux send-keys -t 0:1 'command' Enter` (window 1 is AI server)
+- **Container:** `uncloseai-speech_server_1` (image: `uncloseai-speech:local`)
+- **tmux access:** `tmux send-keys -t 0:1 'command' Enter` (window 0:1 is 3090-ai)
 
 ### Deployment Workflow
 
+**We use git, not rsync.** Commit locally, push, pull on server, rebuild.
+
 ```
 Local:
   /home/fox/git/uncloseai-speech/
 
-  ↓ make deploy (rsync)
+  ↓ git commit && git push
 
-Remote (ai.foxhop.net):
+Remote (3090-ai.foxhop.net):
   /home/fox/git/uncloseai-speech/
 
-  ↓ docker compose up --build
+  ↓ git pull && sudo docker-compose up --build -d
 
 Container:
   /app/
   ├── speech.py
-  ├── voices/
-  │   └── en/en_US/libritts_r/medium/*.onnx
+  ├── voices/samples/  (cloned-voices mounted)
   └── config/
       └── voice_to_speaker.yaml
 ```
@@ -226,28 +227,30 @@ Container:
 ### Quick Production Commands
 
 ```bash
+# Use tmux-hosts to see available tmux windows
+tmux-hosts
+
+# Push changes and deploy
+git add -A && git commit -m "message" && git push
+tmux send-keys -t 0:1 'cd ~/git/uncloseai-speech && git pull && sudo docker-compose up --build -d' Enter
+
 # Check container status
-tmux send-keys -t 0:1 'docker ps' Enter
+tmux send-keys -t 0:1 'sudo docker ps | grep speech' Enter
 
 # View logs
-tmux send-keys -t 0:1 'docker logs -f uncloseai-speech-server-1' Enter
+tmux send-keys -t 0:1 'sudo docker logs --tail 50 uncloseai-speech_server_1' Enter
 
 # Restart container
-tmux send-keys -t 0:1 'cd /home/fox/git/uncloseai-speech && docker compose restart' Enter
-
-# Rebuild and redeploy
-tmux send-keys -t 0:1 'cd /home/fox/git/uncloseai-speech && docker compose up --build -d' Enter
+tmux send-keys -t 0:1 'cd ~/git/uncloseai-speech && sudo docker-compose restart' Enter
 ```
 
 ## Testing Philosophy
 
 **Full stack testing workflow:**
-1. `make clean` - Clean state
-2. `make deploy` - Fresh deploy
-3. `make voices` - Download voice models
-4. `make test` - Basic API test
-5. `make hydrate` - Test all 245 voices (sequential, safe)
-6. `make load-test` - 100 concurrent requests (stress test)
+1. Commit and push changes
+2. Pull on server and rebuild: `git pull && sudo docker-compose up --build -d`
+3. Wait for model to load (check logs)
+4. Test via curl or browser
 
 **Never assume** - always test from scratch after changes.
 
@@ -299,8 +302,8 @@ When running uncloseai-speech as a network service, you must provide:
 ❌ DON'T create directories with raw ssh
 ✅ DO add Makefile target for deployment
 
-❌ DON'T assume container has changes after rsync
-✅ DO rebuild with `make deploy` (runs docker compose up --build)
+❌ DON'T use rsync - we use git
+✅ DO commit, push, pull on server, then rebuild with docker-compose
 
 ❌ DON'T put scripts in docs/
 ✅ DO put scripts in scripts/, reference from docs
@@ -308,16 +311,16 @@ When running uncloseai-speech as a network service, you must provide:
 ❌ DON'T hardcode paths/hosts
 ✅ DO use vars.sh variables
 
-❌ DON'T forget to test from scratch
-✅ DO run `make clean && make deploy && make voices`
+❌ DON'T forget to commit and push before deploying
+✅ DO commit, push, pull on server, rebuild container
 
 ## When Things Break
 
-1. Check `make logs` for errors
-2. Verify Makefile was updated
-3. Test from clean state
-4. Check if container was rebuilt (`make deploy` does this)
-5. Verify voices downloaded (`ls` in container via `make logs` approach)
+1. Check logs: `tmux send-keys -t 0:1 'sudo docker logs --tail 50 uncloseai-speech_server_1' Enter`
+2. Check GPU memory: `tmux send-keys -t 0:1 'nvidia-smi' Enter`
+3. Restart container: `tmux send-keys -t 0:1 'sudo docker-compose restart' Enter`
+4. Rebuild: `git pull && sudo docker-compose up --build -d`
+5. Check voice files: `tmux send-keys -t 0:1 'ls voices/samples/' Enter`
 
 ## Multiprocess Architecture (uvicorn workers=4)
 
diff --git a/sample.env b/sample.env
index 12a70d5..0003f53 100644
--- a/sample.env
+++ b/sample.env
@@ -1,9 +1,10 @@
 TTS_HOME=voices
 HF_HOME=voices
 
-# Worker processes (default: 4 for concurrent TTS requests)
-# Each worker can handle one TTS request at a time
-WORKERS=4
+# Worker processes for concurrent TTS requests
+# Use WORKERS=1 for GPU models like Qwen3-TTS (each worker loads its own model copy)
+# Use WORKERS=4 for CPU models like Piper
+WORKERS=1
 
 #PRELOAD_MODEL=xtts
 #PRELOAD_MODEL=xtts_v2.0.2
diff --git a/speech.py b/speech.py
index 63915aa..190e408 100755
--- a/speech.py
+++ b/speech.py
@@ -1125,8 +1125,20 @@ async def generate_speech(request: GenerateSpeechRequest):
 
         ffmpeg_args.extend(["-"])
         ffmpeg_proc = subprocess.Popen(ffmpeg_args, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
-        ffmpeg_proc.stdin.write(audio_data)
-        ffmpeg_proc.stdin.close()
+
+        # Use threading to avoid deadlock when audio is large
+        # (pipe buffers can fill causing ffmpeg to block on stdout write,
+        # which blocks our stdin write, causing deadlock)
+        def write_audio():
+            try:
+                ffmpeg_proc.stdin.write(audio_data)
+            except Exception as e:
+                logger.error(f"Qwen ffmpeg write error: {e}")
+            finally:
+                ffmpeg_proc.stdin.close()
+
+        writer_thread = threading.Thread(target=write_audio, daemon=True)
+        writer_thread.start()
 
         return StreamingResponse(content=ffmpeg_proc.stdout, media_type=media_type)
     else: