AI Avatar Video

> Install the belt CLI skill: npx skills add belt-sh/cli

AI Avatar & Talking Head Videos

Create AI avatars and talking head videos via inference.sh CLI.

Quick Start

> Requires inference.sh CLI (belt). Install instructions

belt login

Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS)

belt app run pruna/p-video-avatar --input '{ image: https://portrait.jpg, voice_script: Hello, welcome to our product demo!, voice: Zephyr (Female) }'

Available Models

Start with P-Video-Avatar — it's 18x faster and 6x cheaper than alternatives, with built-in TTS, dynamic backgrounds, and 1080p support.

Model	App ID	Best For	Built-in TTS
P-Video-Avatar	pruna/p-video-avatar	Best overall: speed, cost, quality, control	Yes (30 voices, 10 languages)
OmniHuman 1.5	bytedance/omnihuman-1-5	Multi-character, audio-driven	No
Fabric 1.0	falai/fabric-1-0	Image talks with lipsync	Yes
PixVerse Lipsync	falai/pixverse-lipsync	Highly realistic lipsync	No

Cost & Speed Comparison

Model	Speed (per sec of video)	Cost per second
P-Video-Avatar	~1.83s/s	$0.025
OmniHuman 1.5	~28s/s (15x slower)	$0.16 (6.4x more)
Fabric 1.0	~34s/s (18x slower)	$0.14 (5.6x more)

Examples

P-Video-Avatar (Recommended)

Generate avatar from portrait + text script with built-in TTS:

belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Welcome to our product walkthrough. Today I will show you three key features.",
  "voice": "Puck (Male)",
  "voice_language": "English (US)",
  "resolution": "720p"
}'

With custom style control:

belt app run pruna/p-video-avatar --input '{ image: https://portrait.jpg, voice_script: This is exciting news!, voice: Aoede (Female), voice_prompt: Enthusiastic and energetic tone, video_prompt: The person is presenting on stage with dramatic lighting, resolution: 1080p }'

With audio file instead of TTS:

belt app run pruna/p-video-avatar --input '{ image: https://portrait.jpg, audio: https://speech.mp3 }'

### Full Workflow: Generate Portrait + Avatar

Use Pruna P-Image to generate the portrait, then create the avatar:

1. Generate a portrait image

belt app run pruna/p-image --input '{ prompt: professional headshot portrait of a young woman, neutral background, looking at camera, studio lighting, photorealistic, aspect_ratio: 9:16 }'

2. Create avatar video with built-in TTS

belt app run pruna/p-video-avatar --input '{ image: <image-url-from-step-1>, voice_script: Hi there! Let me walk you through our latest features., voice: Zephyr (Female) }'

### OmniHuman 1.5 (Multi-Character)

belt app run bytedance/omnihuman-1-5 --input '{ image_url: https://portrait.jpg, audio_url: https://speech.mp3 }'

Supports specifying which character to drive in multi-person images.

### Fabric 1.0 (Image Talks)

belt app run falai/fabric-1-0 --input '{ image_url: https://face.jpg, audio_url: https://audio.mp3 }'

### PixVerse Lipsync

belt app run falai/pixverse-lipsync --input '{ image_url: https://portrait.jpg, audio_url: https://speech.mp3 }'

## Full Workflow: TTS + Avatar (Non-TTS Models)

For models without built-in TTS (OmniHuman, PixVerse), generate speech first:

1. Generate speech — Inworld TTS-2 for expressive character voices

belt app run inworld/text-to-speech-2 --input '{ text: [friendly] Welcome to our product demo! [excited] Let me show you three features that will change how you work., voice_id: Sarah, delivery_mode: CREATIVE }' > speech.json

2. Create avatar video with the speech

belt app run bytedance/omnihuman-1-5 --input '{ image_url: https://presenter-photo.jpg, audio_url: <audio-url-from-step-1> }'

> **Tip**: For most use cases, P-Video-Avatar with built-in TTS is simpler — no separate audio step needed. Use this workflow only when you specifically need OmniHuman (multi-character) or PixVerse (realistic lipsync).

## Full Workflow: Dub Video in Another Language

1. Transcribe original video

belt app run infsh/fast-whisper-large-v3 --input '{audio_url: https://video.mp4}' > transcript.json

2. Translate text (manually or with an LLM)

3. Generate speech in new language

belt app run infsh/kokoro-tts --input '{text: <translated-text>}' > new_speech.json

4. Lipsync the original video with new audio

belt app run infsh/latentsync-1-6 --input '{ video_url: https://original-video.mp4, audio_url: <new-audio-url> }'

## Avatar UGC Generation

Create UGC-style content with P-Video-Avatar — built-in TTS, no separate audio step needed:

1. Generate a relatable UGC-style portrait

belt app run pruna/p-image --input '{ prompt: casual selfie-style photo of a young woman in a cozy room, natural lighting, looking at camera, warm smile, authentic feel, aspect_ratio: 9:16 }'

2. Create UGC avatar video with built-in TTS

belt app run pruna/p-video-avatar --input '{ image: <image-url-from-step-1>, voice_script: Okay so I just tried this product and honestly? It is a game changer. I was not expecting to love it this much but here we are!, voice: Zephyr (Female), voice_prompt: Excited, casual, authentic tone like talking to a friend, video_prompt: The person is talking casually to camera in their room, natural gestures, resolution: 1080p }'

### Why P-Video-Avatar for UGC

- **All-in-one** — built-in TTS means no separate audio generation step

- **30 voices, 10 languages** — match your target audience

- **Voice + video prompts** — control tone, emotion, body language, and background independently

- **18x faster, 6x cheaper** — produce UGC at scale vs. Fabric/OmniHuman/HeyGen

- **1080p support** — platform-ready vertical video from a single portrait image

### Batch UGC: Same Product, Multiple Presenters

Generate 3 different presenters

for voice in Zephyr (Female) Puck (Male) Aoede (Female); do belt app run pruna/p-video-avatar --input { \image\: \https://portrait.jpg\, \voice_script\: \This changed my morning routine completely. Five minutes and I am done.\, \voice\: \$voice\, \voice_prompt\: \Casual, authentic, like a real testimonial\, \video_prompt\: \Person talking to camera in a bright kitchen\, \resolution\: \1080p\ } done

## Use Cases

- **UGC & Marketing**: Product demos, UGC-style ads with AI presenters

- **Education**: Course videos, explainers

- **Localization**: Dub content across 10 languages from one image

- **Social Media**: Consistent virtual influencer content

- **Corporate**: Training videos, announcements

- **Gaming**: Character avatars, NPC dialogue

## Tips

- Use high-quality portrait photos (front-facing, good lighting)

- Audio should be clear with minimal background noise

- P-Video-Avatar supports built-in TTS — no need for a separate speech generation step

- P-Video-Avatar output aspect ratio matches the input image

- Generate portraits with `pruna/p-image` using `9:16` aspect ratio for vertical videos

- OmniHuman 1.5 supports multiple people in one image

- LatentSync is best for syncing existing videos to new audio

## Related Skills

Dedicated P-Video-Avatar skill

npx skills add inference-sh/skills@p-video-avatar

Full platform skill (all apps)

npx skills add inference-sh/skills@infsh-cli

Text-to-speech (generate audio for non-TTS avatar models)

npx skills add inference-sh/skills@text-to-speech

Speech-to-text (transcribe for dubbing)

npx skills add inference-sh/skills@speech-to-text

Video generation

npx skills add inference-sh/skills@ai-video-generation

Image generation (create avatar images)

npx skills add inference-sh/skills@ai-image-generation

Browse all video apps: `belt app list --category video`

## Documentation

- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI

- [Content Pipeline Example](https://inference.sh/docs/examples/content-pipeline) - Building media workflows

- [Streaming Results](https://inference.sh/docs/api/sdk/streaming) - Real-time progress updates