Image-to-Video AI Models Compared: Cost, Resolution, and Control
Blog post from OpenRouter
OpenRouter compares image-to-video capabilities across Veo, Seedance, Kling, and Grok Imagine Video models, which share a common asynchronous API workflow but differ in duration, resolution, audio, frame control, reference support, and pricing. Image-to-video fixes an image as the first frame, last frame, or both through the `frame_images` field, while reference-to-video uses assets as non-fixed creative guidance through `input_references`; frame images take precedence when both are supplied. Veo supports 4-to-8-second clips with optional audio and up to 4K resolution, Seedance offers the longest outputs of up to 30 seconds and extensive reference-asset support, Kling provides 3-to-15-second 720p clips with first- and last-frame control, and Grok supports 1-to-15-second clips from a first frame only, with version-specific audio and reference features. Model selection should begin with required duration and frame positioning, then consider audio, resolution, reference needs, and cost, which is generally per second except for Seedance’s video-token pricing. The post also outlines submission practices, including using stable direct image URLs, disabling automatic retries for billable generation submissions to prevent duplicate jobs, polling job status every 30 seconds, downloading completed outputs, and querying the models endpoint to validate supported settings and current pricing.
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