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Wan 2.7 is a controllable video model built for teams that need practical knobs instead of black-box generation. It supports text-to-video and image-to-video workflows, gives direct control over ratio, duration, resolution, negative prompting, and seed, and is therefore well suited to repeatable production pipelines rather than one-off experiments. On ImagineGo, it is especially useful for creators who need storyboard-friendly previews, vertical and horizontal variants for distribution, and a model that can translate clear motion direction from a strong still frame. If your workflow depends on taking a concept from static design to motion without losing composition intent, Wan 2.7 is one of the more workable additions in this batch.
Use Wan 2.7 to explore camera motion, pacing, and visual emphasis before committing to heavier editing or post-production. It is well suited to quick storyboard validation and creative alignment across teams.
Its ratio control makes it practical for short-form vertical assets used in TikTok, Reels, Shorts, and paid acquisition testing where several message angles must be turned into motion quickly.
If a team already has still imagery from design, brand, or product marketing, Wan 2.7 can convert those approved visuals into motion concepts without forcing a full visual reset.
Wan 2.7 is useful for lightweight explainer sequences, UI-inspired movement, environment reveals, and scene transitions where precise timing matters less than clean concept communication.
Global teams often need the same visual idea in square, portrait, and landscape formats. Wan 2.7 makes that adaptation easier by keeping the same motion intent across several distribution surfaces.
Short motion clips can improve product pages, feature pages, and comparison articles. Wan 2.7 gives teams a relatively efficient way to create supporting video content for pages that need richer media.
The model supports multiple aspect ratios plus 720p and 1080p output, which makes it practical for product demos, shorts, reels, ad variants, and editorial motion where destination format matters.
Because Wan 2.7 can use a first frame and still respect scene direction, it fits workflows where teams already have a key visual, frame board, or concept render and want to animate from that starting point.
The added prompt-extend and negative-prompt controls help teams shape motion behavior more deliberately, reducing the need to brute-force outputs through repeated blind retries.
When your team uses standard prompt formats, reference frames, and repeatable scene recipes, Wan 2.7 is easier to turn into an operational content system instead of a one-off creative toy.
See credit costs for Wan 2.7 and every other model on the pricing page. Credits never expire.
View all pricingWan 2.7 exposes practical controls such as ratio, duration, resolution, negative prompt, and seed, which makes it easier to use in a repeatable production workflow rather than relying on trial and error.
Use text-to-video when you are still inventing the scene and want broader exploration. Use image-to-video when you already have a key frame, approved visual, or existing concept render that should anchor the motion output.
Yes. Its format control makes it practical for portrait-first social assets, short explainers, ad variants, and creative tests that need to be resized or adapted for several channels.
Negative prompts help remove unwanted movement, clutter, artifacts, and style drift. They are especially useful when you want a cleaner, more controlled result from a reusable template workflow.
Yes. Wan 2.7 is one of the more pipeline-friendly additions because its controls make it easier to standardize prompts, output specs, and scene structures across a repeated production process.
Product marketing teams, growth teams, content teams, and agencies benefit most when they need video assets that are more controllable than purely exploratory motion models.
It can do both, but it is especially strong as a bridge from static creative direction to usable motion. Many teams will use it for storyboard validation, explainers, and medium-value production assets.