Text-to-Video vs Image-to-Video: Which One Should You Start From?

 

Start from an image if you already have a frame you need to keep — a product photo, a portrait, a still from a shoot. Start from text if you are exploring and have nothing to preserve yet. That single question decides it. The expensive part, meanwhile, is not the input type you choose: on the pricing page I checked in November 2026, the same five-second render doubles from 30 credits at 720p to 60 at 1080p — double the cost for resolution alone. This guide breaks down what each workflow is actually for, where the cost really goes, and what neither one can do yet.

I've been cutting short-form video with AI tools for about a year — mostly product clips and social cutdowns. The question I get asked most isn't "which tool is best." It's "should I start from text or from an image?" And nearly everyone asking it treats those as two settings on the same dial.

What is the difference between text-to-video and image-to-video?

The terms get used interchangeably, which is where the trouble starts. Three definitions, because everything else depends on them:

Text-to-video means every frame is generated from a written description. You provide the prompt; the model invents the subject, the lighting, the camera, and the motion. Nothing you already own goes into the output.

Image-to-video means you supply a still frame and the model predicts motion between it and whatever comes next. The subject is yours. Only the movement is invented.

Universal AI credits are a single balance spent across different models, where the cost per render shifts by model and by output resolution rather than staying flat.

How do the two workflows compare?

	Text-to-video	Image-to-video
Input	A written prompt	A still frame you supply
Who owns the subject	The model invents it	You do — the output looks like your source
Best for	Exploring concepts, b-roll, filler shots	Product photos, portraits, bridging cuts
Main weakness	Won't match your product, brand colours or past footage	You suggest motion, you don't direct it — and it stays short
Continuity	Three renders give three similar scenes, not three angles of one scene	One scene, held together, because your frame anchors it

When should you start from text?

When you have no source material and you're not sure what you want yet. It earns its keep in three situations: exploring a concept before you commit to shooting it, generating b-roll you'd otherwise pay to license, and filling gaps in a cut where the specific content doesn't matter — a crowd, a skyline, steam off a coffee cup.

What it will not do is respect anything you already have. Ask it for "our mug on a wooden table" and you'll get a mug on a wooden table, not your mug.

When should you start from an image?

When you already have the frame and motion is the only thing missing. A product photo that needs to rotate slightly. A portrait that should blink and turn toward camera. A frame pulled from a shoot that needs two seconds of movement to bridge a cut.

Fidelity is the whole advantage: the output looks like your source because your source is the input. The tradeoff is control — hands and faces still break often enough that you should plan to discard takes, and a continuous shot with a beginning, middle and end is not realistic. A few seconds is.

Where does the cost actually go?

Here's the part that matters more than which input type you pick. On the pricing page I checked in November 2026, a five-second render costs 30 credits at 720p and 60 at 1080p. Same prompt, same five seconds, double the cost for resolution alone.

So resolution is the lever that moves your balance fastest, not input method. Text-to-video and image-to-video sit in the same ballpark; 720p and 1080p do not.

The fix is almost never switching input types. It's rendering at 720p while you're still iterating and only going up to 1080p on the take you're actually going to publish. Iterating at 1080p is the fastest way to burn through a credit balance on drafts you throw away.

What can neither one do yet?

Neither approach handles these well, and I'd rather say so than have you discover it mid-project:

• Precise camera moves. You can suggest a direction, not a dolly path with a specific focal length.
• Lip sync beyond a few seconds. Short clips hold up. Anything longer drifts.
• Multi-shot continuity. Each render is its own event. There's no scene memory between them.
• Text rendered inside the frame. Logos, labels, captions burned into the image — still unreliable enough to add in post instead.

None of these are close to solved, and I'm not going to pretend a model update quietly fixed them.

So which one should you start from?

One question, five seconds: do you already have a frame you need to keep? Yes — start from the image; you keep everything that's already correct and only generate what's missing. No — start from text; you're exploring, and there's nothing to preserve yet.

Then the budget question: does the final cut need to hold up at 1080p? Plan for it if so. If you're still deciding what the shot should be, render at 720p and save the upgrade for the take you keep.

If you want to run both from the same workspace rather than juggling separate tools, Textideo's image-to-video page sits alongside the text-to-video workflow under one credit balance, which is the practical reason I stopped switching between them.

Why no model ranking in this guide?

I haven't run a controlled comparison — same prompt, same resolution, same seed, three models, conditions written down and published — and I'm not going to imply results I didn't get. Anyone who hands you a ranked list without publishing their conditions is guessing, and the guess is usually shaped by whichever tool they're affiliated with.

If you want a ranking, run it yourself: fix the prompt, fix the resolution, run three models, write down what you changed. That version is the only one worth reading, including if it contradicts something here. And if your results go differently — especially if image-to-video held continuity better than I'm describing — email me. I'd rather correct this post than leave it standing wrong.