Boreal-H3 Text to Video

Generate phone-real UGC video with native dialogue and sound.

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~36.64s
Example output
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Boreal-H3 Text to Video: AI Text-to-Video Model

What is Boreal-H3 Text to Video?

Boreal-H3 Text to Video is Creatify's text-to-video model, a post-train of the MiniMax H3 base narrowed for advertising and short-form social video. Give it a written prompt and it returns a finished clip, 1 to 15 seconds, at 768p, 1088p or up to 2k, with native dialogue and sound on every clip. Its signature is the look: a real-camera, phone-footage aesthetic — vlog, UGC-ad and documentary realism — rather than a graded cinematic sheen, which is exactly what reads as native social and ad creative.

Key Features

  • Prompt-only text to video, with native dialogue and sound baked into every clip.
  • Phone-footage, UGC realism by default — handheld and documentary rather than a polished film grade.
  • Follows the brief as a shot: subject, action and camera direction, with legible cause-and-effect motion.
  • Output at 768p, 1088p or 2k (1440 px on the short edge), 24 fps, H.264 video with AAC audio.
  • Whole-second length from 1 to 15, and six aspect ratios including vertical 9:16 for social.
  • Fast to a finished clip, so you can iterate many variants; prompt_enhancement rewrites or keeps your prompt literal.

Best Use Cases

UGC-style ads and social posts are the sweet spot: talking-head creators, lifestyle and product demos, and quick shot variants for Reels, TikTok and Shorts. Because it renders people and motion that read as genuinely filmed on a phone, and carries its own audio, a single prompt can produce a social-ready cut — a maker talking to camera while they work, a pour that behaves like liquid, a demo where the described action actually happens. The tested default, a ceramicist at a wheel talking to camera, shows the pattern: a real person, a spoken line, and believable motion in one pass.

Prompt Tips and Output Quality

Write the prompt as one shot — subject, action, camera move, and any spoken line in quotes. Name ambient sounds (a wheel humming, a sizzling pan) to fill the audio bed; returned audio runs loud. There is no seed, so vary the prompt to explore different takes. In testing, a 9:16 clip of a potter talking to camera came back with convincing handheld realism, synced speech and clean hand-on-clay motion. Start at 768p to iterate, then re-run the same prompt at 2k for delivery.