Morning coffee
Morning sunlight on a ceramic coffee cup on a wooden table. A gentle slow camera push, steam rising, calm cinematic lighting.
Alibaba
wan2.5-t2vCreate a video from text. Try the real morning-coffee example.
/ second
Estimate the cost first. Generation starts only after confirmation.
Load the original settings, then adjust them before generating.
Morning sunlight on a ceramic coffee cup on a wooden table. A gentle slow camera push, steam rising, calm cinematic lighting.
Create a video from text. Try the real morning-coffee example.
Fields accepted in the request body for this model.
prompttextdurationenumaudio_urlaudio URLsizeenumnegative_prompttextseedintegerprompt_extendboolean1920X1080
Bill actual quantity
Minimum per call: 0 USD · Rounding is applied once to the total cost
Pricing follows the selected specifications
1080X1920
Bill actual quantity
Minimum per call: 0 USD · Rounding is applied once to the total cost
Pricing follows the selected specifications
832X480
Bill actual quantity
Minimum per call: 0 USD · Rounding is applied once to the total cost
Pricing follows the selected specifications
480X832
Bill actual quantity
Minimum per call: 0 USD · Rounding is applied once to the total cost
Pricing follows the selected specifications
1280X720
Bill actual quantity
Minimum per call: 0 USD · Rounding is applied once to the total cost
Pricing follows the selected specifications
720X1280
Bill actual quantity
Minimum per call: 0 USD · Rounding is applied once to the total cost
Pricing follows the selected specifications
Prices are billed per unit consumed with no monthly minimum. See billing guide for USD estimates and actual usage charges.
POST https://orux.top/api/v1/tasksAbout wan2.5-t2v pricing, capabilities and API access on Orux AI.
wan2.5-t2v: Create a video from text. Try the real morning-coffee example.
See the pricing section on this page for wan2.5-t2v pricing and applicable conditions. Charges depend on the selected parameters and recorded usage.
wan2.5-t2v accepts Text and returns Video.
Create an Orux AI API key and send an authenticated POST request to https://orux.top/api/v1/tasks, using wan2.5-t2v as the model identifier. This model uses asynchronous tasks: submit input, then poll the returned task ID for the result. Try the playground on this page and use the API example for the exact request format.