Testing Qwen3 TTS on Google Colab | Is This Open Source TTS Too Slow?
In this video, I test Qwen3 TTS, an open-source text-to-speech and voice cloning model, using a Google Colab notebook created by NeuralFalcon.
We’ll:
Run Qwen3 TTS on Google Colab
Use the official open-source notebook
Test text-to-speech generation
Explore voice cloning and custom voice options
Check performance, speed, and model behavior
Compare it with faster models like LuxTTS and Kokoro TTS
Qwen3 TTS supports:
High-quality speech generation
Voice cloning with reference audio
Audio transcription
Multiple model sizes (up to 1.7B parameters)
⚠️ Honest takeaway:
This model is powerful but HEAVY. On free Google Colab, generation can be slow, especially when using high-quality + transcription modes.
📌 Notebook used in this video:
👉 https://github.com/NeuralFalconYT/Qwe...
⚠️ Please use voice cloning responsibly. Do NOT use this tool for illegal or harmful activities.
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On this channel, I share practical tutorials about:
Google Colab
Open-source AI & TTS tools
Voice cloning experiments
Django & developer workflows
Budget-friendly tech setups
Thanks for watching — see you in the next one.