ComfyUI-Qwen-TTS

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ComfyUI custom nodes for speech synthesis, voice cloning, and voice design, based on the open-source Qwen3-TTS project by the Alibaba Qwen team.

📋 Changelog

• 2026-01-24: Added attention mechanism selection & model memory management features (update.md)
• 2026-01-24: Added generation parameters (top_p, top_k, temperature, repetition_penalty) to all TTS nodes (update.md)
• 2026-01-23: Dependency compatibility & Mac (MPS) support, New nodes: VoiceClonePromptNode, DialogueInferenceNode (update.md)

Key Features

• 🎵 Speech Synthesis: High-quality text-to-speech conversion.
• 🎭 Voice Cloning: Zero-shot voice cloning from short reference audio.
• 🎨 Voice Design: Create custom voice characteristics based on natural language descriptions.
• 🚀 Efficient Inference: Supports both 12Hz and 25Hz speech tokenizer architectures.
• 🎯 Multilingual: Native support for 10 languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian).
• ⚡ Integrated Loading: No separate loader nodes required; model loading is managed on-demand with global caching.
• ⏱️ Ultra-Low Latency: Supports high-fidelity speech reconstruction with low-latency streaming.
• 🧠 Attention Mechanism Selection: Choose from multiple attention implementations (sage_attn, flash_attn, sdpa, eager) with auto-detection and graceful fallback.
• 💾 Memory Management: Optional model unloading after generation to free GPU memory for users with limited VRAM.

Nodes List

1. Qwen3-TTS Voice Design (VoiceDesignNode)

Generate unique voices based on text descriptions.

• Inputs:
  • text: Target text to synthesize.
  • instruct: Description of the voice (e.g., "A gentle female voice with a high pitch").
  • model_choice: Currently locked to 1.7B for VoiceDesign features.
  • attention: Attention mechanism (auto, sage_attn, flash_attn, sdpa, eager).
  • unload_model_after_generate: Unload model from memory after generation to free GPU memory.
• Capabilities: Best for creating "imaginary" voices or specific character archetypes.

2. Qwen3-TTS Voice Clone (VoiceCloneNode)

Clone a voice from a reference audio clip.

• Inputs:
  • ref_audio: A short (5-15s) audio clip to clone.
  • ref_text: Text spoken in the ref_audio (helps improve quality).
  • target_text: The new text you want the cloned voice to say.
  • model_choice: Choose between 0.6B (fast) or 1.7B (high quality).
  • attention: Attention mechanism (auto, sage_attn, flash_attn, sdpa, eager).
  • unload_model_after_generate: Unload model from memory after generation to free GPU memory.

3. Qwen3-TTS Custom Voice (CustomVoiceNode)

Standard TTS using preset speakers.

• Inputs:
  • text: Target text.
  • speaker: Selection from preset voices (Aiden, Eric, Serena, etc.).
  • instruct: Optional style instructions.
  • attention: Attention mechanism (auto, sage_attn, flash_attn, sdpa, eager).
  • unload_model_after_generate: Unload model from memory after generation to free GPU memory.

4. Qwen3-TTS Role Bank (RoleBankNode) [New]

Collect and manage multiple voice prompts for dialogue generation.

• Inputs:
  • Up to 8 roles, each with:
    • role_name_N: Name of the role (e.g., "Alice", "Bob", "Narrator")
    • prompt_N: Voice clone prompt from VoiceClonePromptNode
• Capabilities: Create named voice registry for use in DialogueInferenceNode. Supports up to 8 different voices per bank.

5. Qwen3-TTS Voice Clone Prompt (VoiceClonePromptNode) [New]

Extract and reuse voice features from reference audio.

• Inputs:
  • ref_audio: A short (5-15s) audio clip to extract features from.
  • ref_text: Text spoken in the ref_audio (highly recommended for better quality).
  • model_choice: Choose between 0.6B (fast) or 1.7B (high quality).
  • attention: Attention mechanism (auto, sage_attn, flash_attn, sdpa, eager).
  • unload_model_after_generate: Unload model from memory after generation to free GPU memory.
• Capabilities: Extract a "prompt item" once and use it multiple times across different VoiceCloneNode instances for faster and more consistent generation.

6. Qwen3-TTS Multi-role Dialogue (DialogueInferenceNode) [New]

Synthesize complex dialogues with multiple speakers.

• Inputs:
  • script: Dialogue script in format "RoleName: Text".
  • role_bank: Role bank from RoleBankNode containing voice prompts.
  • model_choice: Choose between 0.6B (fast) or 1.7B (high quality).
  • attention: Attention mechanism (auto, sage_attn, flash_attn, sdpa, eager).
  • unload_model_after_generate: Unload model from memory after generation to free GPU memory.
  • pause_seconds: Silence duration between sentences.
  • merge_outputs: Merge all dialogue segments into a single long audio.
  • batch_size: Number of lines to process in parallel (larger = faster but more VRAM).
• Capabilities: Handles multi-role speech synthesis in a single node, ideal for audiobook narration or roleplay scenarios.

Attention Mechanisms

All nodes support multiple attention implementations with automatic detection and graceful fallback:

Mechanism	Description	Speed	Installation
sage_attn	SAGE attention implementation	⚡⚡⚡ Fastest	pip install sage_attn
flash_attn	Flash Attention 2	⚡⚡ Fast	pip install flash_attn
sdpa	Scaled Dot Product Attention (PyTorch built-in)	⚡ Medium	Built-in (no installation)
eager	Standard attention (fallback)	🐢 Slowest	Built-in (no installation)
auto	Automatically selects best available option	Varies	N/A

Auto-Detection Priority

When attention: "auto" is selected, the system checks in this order:

1. sage_attn → If installed, use SAGE attention (fastest)
2. flash_attn → If installed, use Flash Attention 2
3. sdpa → Always available (PyTorch built-in)
4. eager → Always available (fallback, slowest)

The selected mechanism is logged to the console for transparency.

Graceful Fallback

If you select an attention mechanism that's not available:

• Falls back to sdpa (if available)
• Falls back to eager (as last resort)
• Logs the fallback decision with a warning message

Model Caching

• Models are cached with attention-specific keys
• Changing attention mechanism automatically clears cache and reloads model
• Same model with different attention mechanisms coexists in cache

Memory Management

Model Unloading After Generation

The unload_model_after_generate toggle is available on all nodes:

• Enabled: Clears model cache, GPU memory, and runs garbage collection after generation
• Disabled: Model remains in cache for faster subsequent generations (default)

When to use:

• ✅ Enable if you have limited VRAM (< 8GB)
• ✅ Enable if you need to run multiple different models sequentially
• ✅ Enable if you're done with generation and want to free memory
• ❌ Disable if you're generating multiple clips with the same model (faster)

Console Output:

🗑️ [Qwen3-TTS] Unloading 1 cached model(s)...
✅ [Qwen3-TTS] Model cache and GPU memory cleared

Installation

Ensure you have the required dependencies:

pip install torch torchaudio transformers librosa accelerate

Tips for Best Results

Audio Quality

• Cloning: Use clean, noise-free reference audio (5-15 seconds).
• Reference Text: Providing text spoken in reference audio significantly improves quality.
• Language: Select the correct language for best pronunciation and prosody.

Performance & Memory

• VRAM: Use bf16 precision to save significant memory with minimal quality loss.
• Attention: Use attention: "auto" for automatic selection of fastest available mechanism.
• Model Unloading: Enable unload_model_after_generate if you have limited VRAM (< 8GB) or need to run multiple different models.
• Local Models: Pre-download weights to models/qwen-tts/ to prioritize local loading and avoid HuggingFace timeouts.

Attention Mechanisms

• Best Performance: Install sage_attn or flash_attn for 2-3x speedup over sdpa.
• Compatibility: Use sdpa (default) for maximum compatibility - no installation required.
• Low VRAM: Use eager with smaller models (0.6B) if other mechanisms cause OOM errors.

Dialogue Generation

• Batch Size: Increase batch_size for faster generation (more VRAM usage).
• Pauses: Adjust pause_seconds to control timing between dialogue segments.
• Merge: Enable merge_outputs for continuous dialogue; disable for separate clips.

Acknowledgments

• Qwen3-TTS: Official open-source repository by Alibaba Qwen team.

License

• This project is licensed under the Apache License 2.0.
• Model weights are subject to the Qwen3-TTS License Agreement.