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Wan 2.2 / Text to video

Wan 2.2 frame count, frame rate and duration explained

Frame count and frame rate together determine playback duration, but a generation pipeline can also interpolate, trim or re-encode frames. This is why a request setting is not always the same thing as the final video's metadata. Inspect the downloaded file before making a precise duration claim.

By JollyAIReviewed 2 min read

Keep three quantities separate

Frame count is the number of images in a sequence. Frame rate describes how many are displayed per second. Resolution describes the dimensions of each image. Raising one does not automatically improve the others. A larger frame does not make motion smoother, and a higher playback rate does not prove that more distinct motion was generated.

JollyAI's Wan routes include workflow-specific handling, so a bare number such as 81 frames does not fully specify the delivered file. The homepage Wan demonstration, for example, should be described using its actual encoded metadata rather than only the original request.

Verify before editing

  1. Save the original generated file.
  2. Inspect duration, width, height and frame rate in a media tool or editor.
  3. Check whether any smoothing or interpolation was enabled in the available controls.
  4. Match your delivery timeline intentionally and review the exported result.

Avoid accidental speed changes

Interpreting a clip at a different frame rate can alter its playback speed. If the goal is only to place it into another timeline, use your editor's appropriate conversion behaviour and inspect the result. Keep audio handling separate when the source is silent.

Report results clearly

Say “this downloaded example is this duration and size” rather than treating one file as a universal Wan specification. For performance comparisons, hold requested duration and pixel dimensions as comparable as possible and disclose differences that remain. A short metadata check prevents misleading quality labels and unexpected edits later.

REVIEWED JOLLYAI IMPLEMENTATION

The workflow behind the guide

Written scene → configured Wan text conditioning and sampling → frame decoding → video encoding and any selected post-processing.

Inputs, presets & access
PRO for the reviewed standard Wan T2V route. Use the visible preset; do not infer file metadata from the prompt.
Implementation note
JollyAI runs configured Wan workflows with locally selected checkpoints and adapters. T2V, I2V and first/last-frame are separate routes. Presets and post-processing differ by route. Plan sound separately for the demonstrated silent workflow, and inspect the downloaded file before quoting dimensions or duration.

Configuration reviewed September 20, 2026. Your current playground controls and plans page determine availability. Prompt recipes above are suggestions, not guarantees or claimed test results.

Open Text to video ↗

Sources and useful next steps

The implementation notes describe JollyAI's reviewed local integration. Upstream capabilities and licences may differ from the settings available here.

Found an outdated setting or a reproducible problem? Contact JollyAI with the workflow and job reference. Keep account tokens and private input files out of public reports.

KEEP BUILDING

Continue the workflow.