meta text to video is Meta's research system for turning simple text descriptions into short generated video clips with motion and camera behavior. It also supports editing existing footage, personalized clips from a photo, and separate audio creation for short creative work.
Meta Text to Video: Short Clips From Text
Meta Text to Video: Create short clips from simple descriptions, refine motion and camera language, and edit footage or add audio for social concepts.
Meta Text to Video: Create short clips from simple descriptions, refine motion and camera language, and edit footage or add audio for social concepts.
Research system
What Is Meta Text to Video?
meta text to video is Meta's research system, also described as meta movie gen, using a 30B joint image-video transformer for clips up to 16 seconds at 16fps, plus editing, personalized clips, and separate audio. Availability is unverified.
Text prompt with action: Describe one subject plus one clear action plus a simple setting in meta text to video, then keep camera intent short so motion stays readable.
Short video output window: Expect a short generated clip up to 16 seconds at 16fps, which suits single actions and slow camera moves rather than multi-scene stories.
Motion and camera reasoning: The system is described as reasoning about object motion, subject interaction, and camera movement, so name the move you want explicitly.
Video plus text for edits: To revise existing footage, also described as meta movie gen editing, supply the clip plus a narrow instruction that preserves surrounding content and motion.
Photo plus text personalization: Combine one reference photo with text to request a short personalized clip, while identity preservation and natural movement remain research-level expectations.
Separate audio and gaps: Audio creation is described as separate from video, while exact resolutions, audio specs, and public availability remain unverified, as does meta muse video engine version detail.
Clip ideas
Short Clip Directions Worth Storyboarding First
These storyboard directions show how meta text to video ideas might look as short clips, including automated vertical video ai cuts and instagram reel ai video maker layouts for practice.
Cyclists enjoying a peaceful morning ride across a historic canal bridge in Amsterdam.
A master artisan shaping a ceramic vase on a pottery wheel.
Enjoying a quiet night of stargazing by the campfire under the Milky Way.
Paragliders enjoy a scenic flight over a lush mountain valley and river.
An ancient moss-covered waterwheel turns peacefully beside a tranquil forest stream.
A chef masterfully preparing stir-fried noodles over high heat at a night market.
A lone tree stands against dark storm clouds looming over a sweeping golden wheat field at sunset.
Sea turtles gliding through an underwater kelp forest.
Watch Research Explainers and Breakdowns
Use these explainers to see how meta text to video is described in research coverage, from generation to editing. They provide context for prompts, motion, and revision for short creative work without presenting third party videos as official access.
From Idea to Short Clip
This meta text to video workflow follows a simple meta ai video prompt guide you can use in any generic text to video form. Start with a clear subject and action, add controlled motion, then review the result. The on-page form is a separate hosted generator, so practice the structure here without expecting Meta research output. Change one element per retry to learn what improves stability.
1
Exploring the rugged coastline on a windy afternoon.
Describe Subject and Setting
Write one sentence naming the subject, action, and setting, keeping detail simple for a short clear clip.
2
A lone hiker walking along a scenic coastal trail on an overcast day.
Add Motion Then Generate
Add one motion and one camera move, such as a pan, then generate the first short version to test movement.
3
A thoughtful woman overlooks the ocean from a rugged coastal cliff on a windy day.
Review and Refine Once
Watch motion and camera behavior closely, then change one variable at a time before generating again.
Prompt Patterns That Clarify Motion and Camera Choices
Use this meta ai video prompt guide to describe change clearly and keep realistic video generation meta expectations research-level and brief.
An artisan baker enjoys the craft of tossing fresh pizza dough in a sunlit rustic kitchen."A young baker tosses soft dough high in warm kitchen light, flour drifts slowly wide"
A lone cyclist navigates a rain-slicked urban street on a chilly autumn night."A lone cyclist rides wet street at night while dry leaves swirl fast under bright lamps"
A historic stone lighthouse stands tall on a rocky cliff as waves crash against the shoreline at twilight."Old lighthouse stands at blue dusk as camera pushes in slow while waves rise then calm"
Exhausted musician taking a break in a moody urban alleyway."A tired musician rests in neon alley, vertical close view, soft lens glow, calm blue mood"
A soulful musician playing guitar under the rainlit night sky."Same tired musician in neon alley, vertical close view, now light rain falls, hold framing"
An artisan baker enjoys the craft of tossing fresh pizza dough in a sunlit rustic kitchen."A young baker tosses soft dough high in warm kitchen light, flour drifts slowly wide"
A lone cyclist navigates a rain-slicked urban street on a chilly autumn night."A lone cyclist rides wet street at night while dry leaves swirl fast under bright lamps"
A historic stone lighthouse stands tall on a rocky cliff as waves crash against the shoreline at twilight."Old lighthouse stands at blue dusk as camera pushes in slow while waves rise then calm"
Exhausted musician taking a break in a moody urban alleyway."A tired musician rests in neon alley, vertical close view, soft lens glow, calm blue mood"
A soulful musician playing guitar under the rainlit night sky."Same tired musician in neon alley, vertical close view, now light rain falls, hold framing"
### meta text to video prompt structure note: name subject, motion, camera, then confirm limits
Start with four simple options: a daytime street clip, a quiet interior, a portrait, and an open hillside. The selected source is the daytime street clip, with storefronts, passing people, and steady forward motion. A text instruction requests a localized change plus a style shift, such as evening light and altered shop signs, while keeping buildings, path, and movement intact. The final result in meta text to video, also described as meta movie gen editing, reads as the same street scene with new light and details.
A lone traveler gazes out across the rough sea from a high cliffside path.
Exploring the rugged coastline on a windy afternoon.
A thoughtful moment on a rugged coastline overlooking the ocean waves.
A thoughtful moment by the ocean atop a rugged coastal cliff.
A woman standing on a windy cliff overlooking the ocean.
Selected street input stays recognizable; light and details change in output.
Where Short Generated Clips Fit Best
These three practical jobs suit meta text to video research, with short clips you can test, compare, and revise before committing to longer edits.
Social Teasers and Tests
Test a hook for an instagram reel ai video maker workflow, using one clear action and a slow camera move to judge pacing before full edit.
Product Scene Previews
Preview a product setup or room change using professional ai video from meta ideas, getting a quick visual reference to guide photos, staging, or storyboards.
Storyboard Exploration Drafts
Explore story beats and framing with automated vertical video ai tests, producing short silent drafts that clarify sequence, motion, and camera intent.
Pick one job, keep each test short, and revise motion and framing before expanding to longer edits quickly.
Plans and Access Context for Research
This page tracks research context only. Availability and access remain unverified, so check official Meta materials for current status and next steps.
0123456789,0123456789012345678901234567894,200 Fast Credits Per Month
Access to All Models & Features
20% Less Credit Cost For Generation
7 Concurrent Fast Jobs
Seedance 2.0
Seedance 2.0 Mini & Fast
800+ Viral Video & Image Effects
Priority Queue for All Content
2K & 4K Output for All Images
20% Discount For Extra Credits
2K & 4K Output for All Videos
Early Access to Advanced AI Features
We are constantly evolving. More coming soon!
Personalized video audio
Keep One Face Consistent While Building Sound Separately
meta text to video is described as combining a single reference photo with a short text prompt to generate a personalized clip that keeps facial appearance and natural movement. The research claim is identity preservation for consistent character tests, so creators can check the same person across different actions and framings. Audio is handled as a separate step, created or extended to match tone rather than generated in sync. Exact clip length and professional ai video from meta output specs remain unverified, so treat results as short tests.
A lone traveler walks along a dramatic coastal cliff overlooking the crashing waves of the stormy sea.
If you searched facebook text to video tool, use this research context to set test expectations.
What Each Mode Handles Well
This overview shows how meta text to video modes map to practical work, plus where research detail ends and availability remains unverified.
Capability mode
How it appears in practice
Text to video generation
Generates a short clip up to 16 seconds at 16fps matched to the text prompt.
Joint text to image training
Uses a 30B joint transformer for text to image and video to carry detail across frames.
Localized video edit
Changes a selected region from text while keeping surrounding content and motion intact.
Background and style change
Applies a global background or style shift without reshooting the core action.
Personalized video from photo
Combines a reference photo with text to request identity-preserving motion in a short test.
Separate audio creation
Creates or extends effects and music separately to match tone, not as synced audio.
Motion and camera reasoning
Accounts for object motion, subject interaction, and camera movement when prompts name them.
Naming note on Muse references
Treat meta muse video engine as unverified naming, not a confirmed version or release.
Availability and release status
Do not treat open source video model meta as confirmed release. Access and specs remain unverified.
meta text to video is worth studying as research, not planning around as an available product. The work described as meta movie gen shows a focused short-clip approach with motion, editing, and separate audio, but access and product details remain unverified. Treat open source video model meta as unconfirmed, and practice prompt structure in a generic generator while checking official Meta materials for status.
Motion Control
Why Explicit Motion and Camera Cues Matter
In meta text to video, naming one action and one camera move keeps short takes readable, because the model has less time to establish who moves and how the frame moves. For realistic video generation meta work at research level, simple pans, pushes, and holds support pacing, while stacked actions or fast direction changes can blur subjects and break continuity.
A breathtaking night view of glowing sky lanterns ascending above a historic European city illuminated by warm lights and a winding river.
A vintage steam train chugs across a majestic stone viaduct surrounded by dense mountain forests.
A traditional blacksmith shapes glowing metal on the anvil with hammer strikes, sending fiery sparks flying.
Keep prompts to one subject, one motion, and one camera cue, then test variations in a generic form before adding extra action or speed.
In meta text to video tests, complex motion and crowded interaction are common failure points. Hands, fast contact, and layered movement can blur or shift between frames.
Plan one clear action per short take and review faces, edges, and fine detail closely. Early Make-A-Video limits do not describe the current system, so verify current tool limits before planning.
Common Questions About Generation
Quick answers on meta text to video inputs, outputs, prompts, limits, and research status.
It is Meta's research system turning short text into short clips with motion and camera cues. A meta ai video generator search usually means this work.
meta movie gen is the label often used for the same collection behind meta text to video. It groups generation, editing, personalization, and separate audio.
Request one subject doing one clear action in a simple setting. The work covers motion, interaction, and camera moves, so keep ideas short and readable.
Supply a clip plus text for a localized fix or style change. The aim is to preserve surrounding motion while changing only the described part.
Combine a reference photo with short text to request identity-preserving motion. It suits tests of the same person, but likeness and movement need close review.
Audio is created separately to match tone, not in sync with video. Plan sound as a companion step after the visual test.
Name one action, one optional environmental change, and one camera move. Simple cues like pan or hold keep motion readable across short takes.
Keep takes to one action and expect retries on faces, hands, and fine detail. Detail can shift between frames, so review closely and confirm current limits before planning.
No. Availability, pricing, and commercial rights remain unverified. If you searched facebook text to video tool, treat it as discovery wording and check official Meta materials.
Use the on-page form as a separate generic generator to test one action and one camera move. It does not produce official Meta output.
Test Your Short Clip Idea
Turn a one-sentence idea into a short test clip you can watch, review, and refine right away.
Keep the subject, motion, and camera move simple so each version stays easy to compare side by side.
Adjust one detail at a time, then generate again to see which change improves clarity and pacing.
Use the on-page text to video form as a separate practice space today without expecting official research outputs.
