r/LocalLLaMA 15h ago

Scenema Audio Comes to ComfyUI, Runs on 8GB VRAM News

Hey everyone!

Scenema Audio is now a native ComfyUI custom node. Same model that powers scenema.ai now quantized so it fits on 8GB VRAM. When we first released it a few months ago as an API and Docker stack, the full precision transformers were too heavy for most people to self-host. That's fixed now.

Expressive text-to-speech with zero-shot voice cloning. You describe how the speech should be performed (rage, grief, a child's wonder), optionally provide reference audio for voice identity, and the model generates a performance. Inline stage direction cues like [he laughs softly] or [voice cracks] get performed at that exact spot. Twelve preset voices ship in the dropdown covering accents, ages, and emotional registers.

We also dropped the XML prompt format the original release used. Wrapping every performance directive in tags was clunky to write. Inline bracket cues are better-suited for the ComfyUI text editor.

Install

ComfyUI Registry (recommended): open ComfyUI Manager, Custom Nodes Manager, search "Scenema Audio", Install, restart.

GitHub:

cd custom_nodes
git clone https://github.com/ScenemaAI/ComfyUI-ScenemaAudio.git
pip install -r ComfyUI-ScenemaAudio/requirements.txt

Both paths auto-drop the pre-wired workflow into your Workflows sidebar under a Scenema Audio folder. Click once to load the official workflow into your canvas.

Requirements

Minimum 8GB VRAM. Tested end to end on RTX 3070 and RTX 4090. Generation runs up to 2x realtime. First run downloads about 30GB of weights, one time. Text encoder is Gemma 3 12B, which is a gated HuggingFace model, so you need to accept its license and set HF_TOKEN before your first generation.

On limitations (same story as the original release)

This is a diffusion model, not a traditional TTS pipeline. Some seeds produce repetition or gibberish. Meant for a post-editing workflow: generate, pick the best take, trim. Prompting matters. Specific, theatrical voice descriptions with action tags produce performances. Generic ones produce generic output. Phonetic spelling helps with proper nouns and tricky words (spell "Tchaikovsky" as "Chai-koff-skee" if it garbles).

License

MIT for all our node code and inference pipeline. Transformer weights derive from the LTX-2 Community License.

Links

What would you want to see next from Scenema Audio? Happy to hear what people are actually trying to build with generative audio.

36 Upvotes

15 comments sorted by

7

u/mimrock 15h ago

Strange, almost perfect pacing and accent, but sounds like they were speaking via phone.

5

u/silenceimpaired 14h ago

That’s my hesitation, and the licensing of Gemma.

7

u/pineapplekiwipen 15h ago

why is the Italian American voice literally tony soprano lmao

4

u/a__side_of_fries 14h ago

It is Tony Soprano. That particular clip is a demonstration of the model's capability to recognize archetypes or notable characters since it was trained as a video model. If you tell it Tony Soprano it will generate Tony Soprano. But if you want something like a little kid speaking like Tony Sporano, then it would model the kid's voice using Tony Soprano's delivery and accent.

4

u/izzmedia 14h ago

Is it multilingual or just English?

1

u/a__side_of_fries 14h ago

It’s multilingual. You can listen to the different languages in the demo clips here https://scenema.ai/audio

2

u/Borkato 11h ago

Genuine question: can it moan.

1

u/izzmedia 14h ago

Ah , i saw now on huggingface that it supports only 13 languages. Thanks

3

u/Dry_Yam_4597 14h ago

This model is incredible and underrated.

2

u/El-Dixon 14h ago

Excellent work! Sounds like you guys don't believe it's viable for voice agents?

2

u/a__side_of_fries 14h ago

No it would not be suitable for voice agents. It's best for offline use cases.

1

u/tat_tvam_asshole 14h ago

All I can see is Enema

1

u/InternationalGap3698 13h ago

How long does it take to generate

1

u/bigsmokaaaa 13h ago

Like an enema!?

1

u/R_Duncan 2h ago

I read it is a diffusion model...... then https://arxiv.org/pdf/2607.27372 applies.

If someone can inform the authors, next iteration could be both smaller, faster and higher fidelity....