Prompt · Motion · Sound

Text to Video AI: turn a written scene into an AI video

Write the subject, action, camera, lighting, timing, and sound direction, then create a video with live controls in one workspace.

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Text to Video AI

A prompt that directs motion

State who or what is on screen, what changes, where the camera moves, and how the scene sounds.

Live model and input controls

Choose a current text-to-video model and review the fields it exposes before you generate.

A result you can keep working on

Use the finished video in the same GizAI workspace instead of starting another disconnected flow.

Use cases

Built for work that continues after the first result

Concept and story shots

Turn an outline, script beat, or storyboard note into a visual sequence before production.

Social and campaign clips

Create concise scene-led videos for launches, announcements, and editorial posts.

Explainers and visual prototypes

Show a process, product idea, or environment when a static image is not enough.

First-hand examples

Real prompts, settings, results, and tradeoffs

Every example below pairs a visible result with the prompt and generation conditions used to make it useful.

LTX-2.3 Distilled 1.1

Direct text-to-video mountain shot

Input
Text prompt only
Settings
960×528 result · 4.04 seconds · landscape
Prompt

A trekker making their way up a snow-covered mountain trail, with breathtaking views of snow-capped peaks and a clear blue sky overhead, exuding a sense of adventure and tranquility.

What this demonstrates

A single subject, one action, and a clear environment are enough to establish a readable shot without a reference image.

Watch for

The prompt does not explicitly direct the camera or sound, so those details are left to the model.

LTX-2.3 Distilled 1.1

Text-to-video with synchronized audio direction

Input
Text prompt with sound direction
Settings
960×512 result · 4.04 seconds · audio enabled
Prompt

A musician passionately playing an acoustic guitar on a dimly lit stage, with the strings vibrating and the sound resonating through the intimate venue.

What this demonstrates

Naming the sound source in the same shot gives the audio-visual model a concrete event to synchronize.

Watch for

Generated performance audio is illustrative; timing, fingering, and musical accuracy still require human review.

LTX-2.3 Distilled 1.1

Text-to-image-to-video workflow

Input
Text prompt with generated first frame
Settings
960×512 result · 4.04 seconds · Generate Image enabled
Prompt

A unicorn gracefully walking through an enchanted forest, its mane flowing gently in the breeze. The forest is illuminated by soft, magical lights with sparkling dust swirling around, creating a serene and mystical atmosphere.

What this demonstrates

Generating the first frame before motion is useful when the visual design needs approval before animation.

Watch for

The extra image-generation step adds another source of variation and should be reviewed separately from motion.

LTX-2.3 Distilled 1.1

Camera-led neon story shot

Input
Detailed text prompt
Settings
832×448 result · 4.04 seconds · camera and ambience directed
Prompt

A calm cinematic sci-fi shot in a neon-lit rainy alley at night. A scratched white service robot walks beneath a paper umbrella as the camera tracks alongside it from puddle level. Steam rises from a vent, reflections ripple around its feet, and the audio blends rain, soft servos and distant city traffic.

What this demonstrates

Subject, camera height, motion, environmental effects, and sound can coexist when they describe one continuous shot.

Watch for

More simultaneous details increase the chance that a secondary element is simplified or omitted.

LTX-2.3 Distilled 1.1

Stylized stop-motion direction

Input
Detailed text prompt
Settings
832×448 result · 4.04 seconds · stylized materials and sound
Prompt

A charming stop-motion shot opens on a tiny clay coffee shop built from cardboard and painted wood. A round clay barista slides a miniature cup toward a sleepy customer as the camera pans from the espresso machine and pushes into the wobbling curl of steam. Handmade texture, espresso hiss and gentle acoustic guitar.

What this demonstrates

Material words such as clay, cardboard, and painted wood establish a coherent visual language better than a vague style label.

Watch for

Fine object interaction such as hands, cups, and steam can vary between generations.

Recommended models

Good starting points for this workflow

LTX-2.3 Distilled 1.1

Unified audio-video model for fast text-to-video, image-to-video, references, keyframes, and guided motion.

Choose it for fast iteration when your workflow may need text, image, audio, references, keyframes, or guided motion controls.

Inputs
text, image, audio
Output
video
References
Up to 500 images
Resolution
128–2048 px
Duration
1–20 sec
Formats
MP4 · WEBM · MOV
Estimated time
2 ~ 5 min
Included allowance
2 per 48 hours

Sora 2

OpenAI video model for cinematic text-to-video and image-to-video with strong prompt adherence.

Choose it for a text- or image-driven cinematic video prompt when its available settings fit the shot you want.

Inputs
text, image
Output
video
Resolution
720p
Duration
4 · 8 · 12 sec
Estimated time
50 ~ 80 sec
Included allowance
1 per 48 hours
Limits and failure modes

What this tool does not guarantee

These are practical boundaries to check before using a generated clip in production.

Prompt adherence is probabilistic

A model can simplify, omit, or reinterpret requested details. Treat the first result as an iteration, not a guaranteed final shot.

Continuity weakens as complexity grows

Multiple characters, scene changes, precise hand actions, and readable text are harder to keep stable in one generation.

Generated media still needs review

Check identity, anatomy, claims, copyright, safety, and platform requirements before publishing or using a result commercially.

Clear answers

Text to Video AI FAQ

What should I write in a text-to-video prompt?

Lead with the subject and action. Add setting, camera movement, lighting, timing, dialogue, and sound when each one changes the intended result.

Which model should I choose for text to video?

Choose from the live controls based on the source material and control you need. The model guide explains the practical distinction; the generator shows current available inputs and limits.

Can I use text-to-video results in another GizAI task?

Yes. The generator opens the same GizAI workspace, so the prompt, selected model, files, and resulting media remain available for the next step.

How long does text-to-video generation take?

It depends on the selected model, duration, resolution, and queue. The model comparison on this page reads the current estimated time from the live GizAI catalog.

Can text-to-video generate sound or dialogue?

Some video models support synchronized audio or audio guidance. Choose a model whose live input contract includes the audio capability you need and describe the sound source clearly.

Why did the model ignore part of my prompt?

Prompts with many subjects, actions, scene changes, camera moves, and sound events compete for attention. Reduce the request to one assessable shot, then add only details that materially change it.

Can I publish an AI-generated video commercially?

Review the selected model terms and your rights to every reference, brand, likeness, audio element, and claim. Generated output still needs human legal, safety, and quality review.

Is the first result guaranteed to match the prompt?

No. Video generation is probabilistic. Use the visible examples as prompt patterns, compare the result with your brief, and iterate on the failed constraint.

Who and how

How this page was produced and checked

Prepared by
GizAI Product Team
Reviewed by
GizAI Model Operations
Last reviewed

GizAI publishes this page about its own product. Examples are existing GizAI media assets paired with their recorded prompts and settings; model names, inputs, limits, and allowances are rendered from the live model catalog instead of copied into editorial claims.

  1. Confirm that every prompt, poster, and video is visible on the page and served from a stable public URL.
  2. Read model labels, modalities, resolution, duration, estimated time, and included allowance from the live GizAI model contract.
  3. Record what each result demonstrates and a concrete limitation instead of presenting every output as flawless.
  4. Verify the executable form, canonical URL, metadata, structured data, internal links, desktop, mobile, and dark mode in a real browser.

Sources and live contracts

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