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Multimodal AI video tools let creators guide a shot with more than words: a still image can anchor its look, a reference clip can guide composition, and first and last frames can constrain its endpoints. Text still matters, especially for describing movement, timing, and camera behavior. The exact controls depend on the model, so check the named product and version rather than assuming features carry across a platform.
What changes when video generation becomes multimodal?
In text-to-video, a prompt asks the model to invent the scene, subject, action, and visual character. That leaves many visual choices open. With multimodal workflows, you can provide visual material as well as text, giving the model a more concrete starting point or constraint.
- Text-to-video: The prompt describes the scene and often its camera direction; the model resolves the visual details.
- Image-to-video: A still supplies visual information such as composition, subject, lighting, and style. Text can focus on what should move.
- First/last-frame control: Images define the shot’s beginning and ending compositions, constraining the transition between them.
- Video reference or extension: A clip can guide composition, or an existing generated sequence can be extended where the model supports it.
These approaches solve different control problems; none is a universal guarantee that every detail will remain consistent. Providers document particular workflows, not a shared standard across all models.
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- Choose a clear still. The image establishes the visual starting point. Blurring, visible artifacts, or visual cues that imply a different movement can affect the generated motion.
- Describe movement rather than re-listing the image. Runway’s image-to-video prompting guide recommends using the image for visible content and concentrating the prompt mainly on motion.
- Specify the important action and camera behavior. State what the subject does, how the environment moves, and whether the camera pans, tilts, or pushes in. Include direction, speed, or timing when they matter.
- Keep the requested movement plausible for the still. A pose or scene that conflicts with the requested action can make the result harder to control.
- Iterate on the motion instruction. Start with the most important movement; if the result misses it, revise that instruction rather than adding unrelated scene description.
For example: “The camera slowly pushes in as the subject turns toward the window. The curtain moves gently in the breeze.” This describes movement and camera behavior without repeating details the still already shows.
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How do I control motion in image to video?
Give the model specific, compatible movement cues. Separate the subject’s action from environmental motion and camera motion so it is clear what should move. Direction and speed can make an instruction more concrete; timing helps when motion needs to unfold in a particular order. A prompt cannot reliably overcome conflicting cues in the reference, so inspect the still for implied motion before changing the words.
Runway’s guidance is product-specific. Other tools may respond differently, and prompt behavior should not be assumed to transfer unchanged between models.
How do first and last frames control a generated video?
Endpoint images constrain the composition at the start and finish of a shot. The model generates the movement between them, rather than beginning from an unconstrained text description alone. Google documents first- and last-frame inputs as a way to control shot composition in Veo; Adobe describes generating video using uploaded first and last frames with keyframe cropping in Firefly.
Endpoint control is distinct from image-to-video with a single starting still: it supplies a destination as well as a starting composition. It does not, by itself, establish that every intermediate frame will match a particular reference.
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How do I make a video match a reference clip?
First determine what “match” means for the shot. A reference may be intended to guide composition, not reproduce every action or detail. Adobe’s July 17, 2025 Firefly announcement described transferring composition from an uploaded reference video. Google’s Veo documentation describes extending a Veo-generated clip, which uses an existing sequence as input for a different purpose.
Check the product’s stated control before choosing a reference: composition transfer, extension, and generating between endpoint frames are not interchangeable. No universal exact-match guarantee is established by these feature descriptions.
What do current product examples actually support?
These are documented, version- and date-specific examples, not a quality ranking. Feature sets and access can change.
| Product or source | Documented inputs or controls | Important qualification |
|---|---|---|
| Google Veo 3.1 | One or more image inputs, first and last frame inputs, and extension of generated video. | Google’s Veo documentation says extension is not supported in Veo 3.1 Lite. Confirm current model and access details in the documentation. |
| Runway model catalog | The catalog describes Gen-4.5 as text-to-video and image-to-video, and lists other models with reference inputs and in-context editing. | Capabilities differ by model. The model catalog is subject to change; do not infer that one model has every platform feature. |
| Adobe Firefly, as announced July 17, 2025 | Reference-video composition, style presets, aspect ratios, and first/last-frame keyframe cropping. Adobe also announced partner-model availability in Firefly Boards and Generate Video. | This is a dated announcement, not confirmation of current partner availability or plan entitlement. |
| OpenAI Sora, historical context | Its capability page described text-to-video, image-to-video, and video extension or fill. | OpenAI states that Sora was no longer available as of April 26, 2026. It should not be treated as a current option on the basis of its older capability description. |
How should you compare multimodal video models?
Start with the inputs and controls needed for your shot, then verify practical access. A feature name alone does not tell you whether a workflow fits your project.
- Accepted inputs: text, still images, video, or audio references, as supported by the specific model.
- What the reference controls: subject appearance, style, composition, motion, or beginning and ending frames.
- Motion workflow: whether you can direct movement with text and how the model handles the visual cues in the input.
- Editing and extension: whether it can edit within a sequence, transfer composition, or extend a generated clip.
- Output and access: check output requirements, duration, integration, geography, plan eligibility, and current usage cost in the product’s current documentation.
The official sources cited here do not provide a neutral, matched-quality benchmark across providers. Feature lists can help you shortlist tools, but they do not establish which model produces the best result for your footage or prompt.
What about commercial use and rights?
Adobe has described its Firefly models as commercially safe and said they are trained on assets it has permission to use. That is Adobe’s statement about its models, not a substitute for reviewing the terms for the specific product, plan, and project or confirming rights to uploaded reference material. Adobe’s February 12, 2025 announcement also reported more than 18 billion assets generated across the Firefly family; that company-reported figure concerns the family overall, not video generation alone.
Why references help—and where they can fall short
References reduce the number of visual decisions left to a text prompt. They can anchor a starting composition, define endpoints, or guide a composition from a clip. Text remains useful for specifying how the shot changes. But input quality and model behavior still matter: artifacts or implied movement in a still can influence the output, and different products expose different controls. Treat reference guidance as a way to narrow the generation task, not as proof of exact consistency.
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