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