image-to-video
Wan-2.1 FLF2V converts a start and end frame into a smooth, coherent video sequence, bridging frames with realistic motion transitions. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
Your request will cost $0.3 per run.
For $10 you can run this model approximately 33 times.
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ExamplesView all
README
Wan FLF2V — wavespeed-ai/wan-flf2v
Wan FLF2V is a first-last-frame-to-video model that generates a short video by interpolating a coherent motion path between a first_image and a last_image, guided by an optional text prompt. Provide the starting frame and the ending frame, then describe what happens in between (e.g., a transformation, assembly, reveal, or scene change). The model produces a smooth transition clip while keeping the beginning and ending states aligned with your provided frames.
Key capabilities
- First-last-frame guided video generation (first_image → last_image)
- Prompt-guided in-between action and transformation logic
- Supports negative_prompt to reduce artifacts and unwanted motion
- Size selection for different output resolutions
- Seed control for reproducible results
Use cases
- Transformation sequences (frame → completed object, sketch → final render)
- Product assembly and reveal animations (parts → finished product)
- Before/after transitions (makeover, restoration, environment change)
- Visual storytelling between two keyframes for ads and social
- Storyboard “in-betweening” from a first and last shot
Pricing
| Mode | Size tier | 5s | 10s |
|---|---|---|---|
| Standard | Non-720p size | $0.30 | $0.45 |
| Fast | Non-720p size | $0.15 | $0.225 |
| Standard | 720p size (1280×720 / 720×1280) | $0.40 | $0.60 |
| Fast | 720p size (1280×720 / 720×1280) | $0.25 | $0.375 |
Inputs
- first_image (required): starting frame
- last_image (required): ending frame
- prompt (optional): describe the transition and what happens in between
- negative_prompt (optional): what to avoid (blur, jitter, distortion, artifacts)
Parameters
- duration: video length in seconds
- size: output resolution selection (e.g., 832×480)
- num_inference_steps: sampling steps
- guidance_scale: prompt adherence strength
- seed: random seed (-1 for random; fixed value for reproducible results)
Prompting guide (FLF2V)
A good prompt explains how the first becomes the last:
Template: Fixed camera. Start exactly from the first image and end exactly at the last image. In between, show [mechanism] smoothly and coherently. No flicker, no warping.
Example prompts
- Transform the car frame into a complete vehicle. Parts assemble step-by-step, bolts tighten, panels slide into place, paint and reflections appear gradually, cinematic lighting, smooth motion, fixed camera.
- A rough clay sculpture becomes a polished ceramic statue, cracks heal, glaze forms, subtle dust motes, steady camera, seamless transition.
- A bare room becomes fully furnished, objects slide into place naturally, lighting stays consistent, no jitter.