Fabric 1.0 Image to Video

veed/fabric-1.0
VEED Fabric 1.0 is an image-to-video API that turns any image into a talking video
Inference
Commercial use
Partner

Input

Result

Idle

What would you like to do next?

480p - $0.08 per second, 720p - $0.15 per second

Logs

VEED Fabric 1.0 | [image-to-video]

VEED's Fabric 1.0 transforms static images into talking videos at $0.08-$0.15 per second of output. Trading broad animation capabilities for specialized lip-sync precision, the model accepts any image and audio input, synchronizing mouth movements to speech with resolution options up to 720p. Built for avatar creation and video personalization workflows where realistic speech animation matters more than general motion generation.

Use Cases: Talking Avatar Creation | Video Personalization | Educational Content | Marketing Videos


Performance

Fabric 1.0 operates in a specialized niche, image-to-video with audio-driven lip synchronization, where pricing scales with output duration rather than per-inference costs common in other video generation models.

MetricResultContext
Resolution Options480p, 720pTwo quality tiers balancing cost and visual fidelity
Cost per Second$0.08 (480p), $0.15 (720p)Duration-based pricing scales with video length
Input RequirementsImage + AudioDual-input architecture for synchronized lip animation
Output FormatMP4 videoStandard web-compatible format for immediate deployment
Related EndpointsFabric 1.0 FastSpeed-optimized variant trading accuracy for faster generation

Audio-Synchronized Animation Architecture

Fabric 1.0 uses a dual-input pipeline that processes both visual and audio data streams simultaneously, contrasting with standard video generation models that rely solely on text prompts or single-image inputs. The model analyzes audio waveforms to extract phoneme timing and intensity, then maps these features to facial keypoints for realistic mouth movement synthesis.

What this means for you:

  • Precise Lip-Sync Control: Audio-driven animation ensures mouth movements match speech timing and phonetics, eliminating the manual keyframe work required in traditional animation workflows

  • Flexible Input Handling: Accepts any image format (JPG, PNG, WebP, GIF, AVIF) paired with common audio formats (MP3, OGG, WAV, M4A, AAC) via URL or direct upload through the fal API

  • Resolution Flexibility: Choose 480p for rapid prototyping and cost efficiency or 720p for production-quality output based on your deployment requirements

  • Single-API Simplicity: One endpoint handles the entire image-to-talking-video pipeline, eliminating the need to chain separate face detection, audio analysis, and video synthesis services


Technical Specifications

SpecDetails
ArchitectureVEED Fabric 1.0
Input FormatsImages: JPG, JPEG, PNG, WebP, GIF, AVIF; Audio: MP3, OGG, WAV, M4A, AAC
Output FormatsMP4 video
Resolution Options480p, 720p
LicenseCommercial use permitted (Partner model)

API Documentation | Quickstart Guide | Enterprise Pricing


How It Stacks Up

MuseTalk Image to Video ($0.04 per inference) – Fabric 1.0 uses duration-based pricing ($0.08-$0.15/second) versus MuseTalk's per-inference model, making direct cost comparison dependent on output length. MuseTalk offers fixed-cost predictability for budget planning, while Fabric 1.0's tiered resolution system provides quality-cost flexibility for different production requirements.

Kling Video v2.6 Pro Image to Video (pricing varies) – Fabric 1.0 specializes in audio-synchronized talking videos with dual-input architecture, while Kling v2.6 Pro handles broader image-to-video animation including camera movements and scene dynamics. Kling suits general video generation workflows; Fabric 1.0 optimizes specifically for lip-sync accuracy in avatar and personalization use cases.

Fabric 1.0 Fast (reduced pricing) – The Fast variant trades animation quality and precision for faster generation speeds at lower cost, ideal for high-volume applications where approximate lip-sync suffices. Standard Fabric 1.0 prioritizes accuracy and output quality for production deployments where speech synchronization fidelity matters.