Elevenlabs just got wrecked. This free AI text to speech is WILD!
Qwen3 TTS provides AI filmmakers with a powerful, free, and open-source local alternative for dialogue generation and voice cloning without relying on paid commercial APIs.
What this lesson covers
This video reviews Alibaba's Qwen3 TTS, an open-source text-to-speech model capable of advanced emotion control, accent replication, and instant voice cloning. The creator demonstrates setting up and running the model locally inside ComfyUI using custom nodes.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:13 ↗
Alibaba's Qwen3 TTS allows users to generate voices using text prompts, pre-built voices, or instant voice cloning with just a few seconds of audio.
- 00:50 ↗
The model supports detailed prompt-based emotion control, letting creators define pacing, laughter, age, tone, and sudden shifts in sentiment.
- 04:18 ↗
Instant voice cloning accurately preserves speaker identity and can even translate cloned voices into different languages like Japanese.
- 06:51 ↗
Running locally on consumer hardware allows rapid offline generation of diverse accents and multi-voice podcast transcripts.
Workflow outlined in the video
- Clone the ComfyUI-Qwen-TTS repository into your ComfyUI custom nodes directory.
- Install the required Python dependencies listed in the requirements.txt file.
- Launch ComfyUI and load the Qwen3 TTS workflow nodes.
- Input your text transcript and configure voice cloning references or emotion prompts to generate dialogue.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
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How to interpret the numbers
563,791 views captured 23 October 2026. ReelStack recommendation score: 66/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 5.29× views vs 12 other channel videos observed at a similar age. View-evidence factor 100% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 1066 views/day vs 6 channel baseline (7 comparable uploads), with the same view-evidence factor
- 10% engagement: 88/100; likes + 4× comments, smoothed with a 500-view neutral prior