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, generate speech first:

# 1. Generate speech from text
belt app run infsh/kokoro-tts --input '{
  "prompt": "Welcome to our product demo. Today I will show you..."
}' > 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>"
}'

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>"
}'

Use Cases

• Marketing: Product demos with AI presenter
• Education: Course videos, explainers
• Localization: Dub content in multiple languages
• Social Media: Consistent virtual influencer
• 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 250+ 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 - How to run apps via CLI
• Content Pipeline Example - Building media workflows
• Streaming Results - Real-time progress updates