Vidu Q1 Text to Video

Vidu Q1 Text to Video specializes in the vidu/q1/text-to-video workflow for text to video work in video production. Vidu Q1 is Shengshu's text-to-video AI model. Turn written scripts and prompts into professional-quality video clips with realistic motion, lighting, and scene composition. Teams can place this named operation inside review, asset preparation, and publishing pipelines while keeping the original request attached to every result. The endpoint is especially useful when a project has a defined transformation goal and needs a repeatable request contract instead of an ad-hoc desktop step. Because vidu/q1/text-to-video is a separate catalog entry, evaluations should use this route’s own inputs, output expectations, and billing behavior. This is the creative remit of the exact endpoint, not a family-wide promise.

For example, the route documentation includes “In an ultra-realistic fashion photography style featuring light blue and pale amber tones, an astronaut in a spacesuit walks through the fog. The background consists of enchanting white and golden lights, creating a minimalist still life and an impressive panoramic scene.”. The mandatory portion is prompt. seed controls seed for the random number generator; style controls the style of output video; style accepts general, anime; prompt controls text prompt for video generation, max 1500 characters; aspect ratio controls the aspect ratio of the generated image; aspect ratio accepts 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16; movement amplitude controls the movement amplitude of objects in the frame; movement amplitude accepts auto, small, medium, large. Vidu Q1 Text to Video exposes seed, style, prompt, aspect_ratio, movement_amplitude as its documented request surface. Applications can submit that exact shape asynchronously, retain the chosen arguments in job metadata, and collect the resulting media URL for review or publishing.

Highlights

• Coherent motion. Vidu Q1 Text to Video is built to turn the route’s text or reference media into a temporally connected sequence rather than unrelated frames.
• Shot direction. Prompts can describe subject action, camera movement, pacing, and atmosphere so Vidu Q1 Text to Video has a concrete motion plan.
• Reference-aware generation. When this route accepts source media, Vidu Q1 Text to Video uses it to anchor identity, composition, or the clip boundary throughout generation.
• Production variants. Declared duration, resolution, framing, or inference controls support repeatable video options for review and selection.

Pricing

When to Use

Prompt Guide

Lead with the subject or transformation, then add the composition, environment, style, lighting, motion, voice, or fidelity details relevant to this route. Keep every parameter inside the documented schema; the example below uses only fields declared for vidu/q1/text-to-video.

{
  "prompt": "In an ultra-realistic fashion photography style featuring light blue and pale amber tones, an astronaut in a spacesuit walks through the fog. The background consists of enchanting white and golden lights, creating a minimalist still life and an impressive panoramic scene.",
  "style": "general",
  "aspect_ratio": "21:9",
  "movement_amplitude": "auto"
}

Technical Specs

Related Models

• vidu/q3/text-to-video
• vidu/q3/image-to-video
• vidu/q3/reference-to-video/mix
• vidu/q3/image-to-video/turbo