ai-avatar-video
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Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human
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Sourceinference-skills/skills
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NPX Install
npx skill4agent add inference-skills/skills ai-avatar-videoTags
Translated version includes tags in frontmatterSKILL.md Content
View Translation Comparison →AI Avatar & Talking Head Videos
Create AI avatars and talking head videos via inference.sh CLI.

Quick Start
Requires inference.sh CLI (). Install instructionsbelt
bash
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 | | Best overall: speed, cost, quality, control | Yes (30 voices, 10 languages) |
| OmniHuman 1.5 | | Multi-character, audio-driven | No |
| Fabric 1.0 | | Image talks with lipsync | Yes |
| 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:
bash
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:
bash
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:
bash
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:
bash
# 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)
bash
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)
bash
belt app run falai/fabric-1-0 --input '{
"image_url": "https://face.jpg",
"audio_url": "https://audio.mp3"
}'PixVerse Lipsync
bash
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:
bash
# 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
bash
# 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 using
pruna/p-imageaspect ratio for vertical videos9:16 - OmniHuman 1.5 supports multiple people in one image
- LatentSync is best for syncing existing videos to new audio
Related Skills
bash
# 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-generationBrowse all video apps:
belt app list --category videoDocumentation
- Running Apps - How to run apps via CLI
- Content Pipeline Example - Building media workflows
- Streaming Results - Real-time progress updates