Video Concatenate: Dual Video Merging Model

What is Video Concatenate?

Video Concatenate is a specialized AI model designed for seamless video merging workflows. It combines two video inputs into a single output file, offering developers precise control over orientation (horizontal or vertical), spacing, size normalization, and audio selection. Built for automation, this model handles the complexity of video format alignment, resolution matching, and encoding optimization—eliminating manual video editing steps in production pipelines. Whether you're building social media tools, comparison dashboards, or multi-camera recording systems, Video Concatenate provides API-first video processing with consistent, high-quality results.

Key Features

• Flexible concatenation directions: Merge videos side-by-side (horizontal) or stacked (vertical) based on layout needs
• Intelligent size adjustment: Three scaling modes—reduce largest, magnify smallest, or crop—to ensure uniform dimensions
• Customizable spacing and color: Add pixel-perfect gaps between videos with hex color control for branded separators
• Selective audio preservation: Choose audio from either video or remove it entirely for silent outputs
• Quality and speed optimization: CRF values (0-51) and encoding presets (ultrafast to veryslow) balance file size, quality, and processing time
• Multi-language SDK support: Ready-to-use code examples in Python, JavaScript, Go, PHP, and Ruby for rapid integration

Best Use Cases

Social Media Content Creation: Generate split-screen comparison videos, before/after transformations, or reaction videos with synchronized playback.

E-Learning Platforms: Combine instructor footage with screen recordings or presentation slides for educational content.

Sports and Gaming Analysis: Create side-by-side performance comparisons, replays with commentary, or multi-angle event coverage.

Product Demonstrations: Showcase product features alongside user testimonials or competitive comparisons in marketing materials.

Surveillance and Monitoring: Merge camera feeds from different angles for security review or incident analysis dashboards.

Prompt Tips and Output Quality

Video Input Guidelines

• Match source quality: Use videos with similar resolutions and frame rates to avoid scaling artifacts. 1080p or higher recommended.
• Format compatibility: MP4 with H.264 encoding works best. Verify URLs are publicly accessible before processing.

Parameter Optimization

• Spacing: Start with 10-20px for subtle separation; increase to 50+ for clear visual boundaries in horizontal layouts.
• Size adjustment: Use reduce_biggest to prevent upscaling blur, or crop_biggest when aspect ratio consistency matters more than full frames.
• CRF sweet spot: Values between 18-28 balance quality and file size—24 is ideal for web delivery, 18 for archival quality.
• Encoding presets: Choose fast for quick iterations during development, medium for production, slow for final renders requiring maximum compression efficiency.

Audio Selection Strategy

• Select video1 for primary narration preservation, video2 for background music retention, or none for voiceover workflows.

FAQs

What video formats does Video Concatenate support?
The model accepts MP4 videos with H.264 encoding via HTTPS URLs. Other formats may process but could produce inconsistent results.

How does size adjustment affect video quality?
reduce_biggest downscales the larger video to match the smaller one, preserving sharpness. magnify_smallest upscales but may introduce blur. crop_biggest maintains resolution by trimming excess dimensions.

Can I concatenate videos with different aspect ratios?
Yes. The size adjustment parameter handles mismatched dimensions, though reduce_biggest or crop_biggest produces the most visually consistent results.

What's the difference between CRF values?
Lower CRF (0-18) = higher quality, larger files. Higher CRF (28-51) = compressed quality, smaller files. CRF 24 offers near-lossless quality with reasonable file sizes for most applications.

Which encoding preset should I use for production?
fast balances speed and compression for real-time applications. medium is recommended for production workflows requiring efficient encoding. slow or slower maximize compression efficiency when processing time isn't critical.

Does the model preserve video metadata and embedded subtitles?
The model focuses on visual and audio concatenation. Metadata like timestamps and subtitles may not transfer—re-apply them post-processing if needed.