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This article provides a technical comparison of leading image-to-video models (Veo 3.1, Seedance, Kling, and Grok) regarding their specific constraints on duration, resolution, frame control, and pricing per second. It details the API lifecycle for submitting these jobs via TypeScript SDKs, offering developers concrete data to select the optimal model for their generative video workflows.
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Best Image-to-Video AI Models in 2026: Cost, Resolution, and Control

OpenRouter10 min de cititArticolul și perspectiva sunt în engleză.

If you already have the image a video should start from, the model choice comes down to what has to happen after that frame. We compared the 26 models in our video catalog that accept a starting frame on duration, resolution, frame control, audio, reference inputs, and price per second, then show how to submit an image-to-video job with the TypeScript SDK.

If you already have the image a video should start from, choosing an image-to-video model comes down to what has to happen after that first frame. The clip may need to end on a second exact image, run longer than a few seconds, include generated audio, or stay under a price per second. The video models we serve handle those requirements differently. This post covers four model lines: Veo 3.1, Seedance, Kling, and Grok Imagine Video. They are not the whole image-to-video catalog. The video models collection has the full list. You call all of them through the same video generation API. The submit, poll, and download lifecycle is the same for every model. The durations, resolutions, frame roles, audio options, and prices each model accepts are not. This post compares those settings, then shows how to submit an image-to-video job with the TypeScript SDK. Veo 3.1, Fast, and Lite generate 4, 6, or 8 second clips with first-frame and last-frame control and generated audio. Veo 3.1 and Fast go up to 4K, Lite stops at 1080p. Seedance 2.5 generates 4 to 30 second clips at 480p or 720p, accepts first and last frames, and takes up to 50 image,…

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