lora-support
WAN 2.1 T2V 480p delivers ultra-fast text-to-video generation with custom LoRA support for unlimited 480p AI videos. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Input
Idle
Votre requête coûtera $0.125 par exécution.
Pour $10 vous pouvez exécuter ce modèle environ 80 fois.
ExemplesTout voir
README
Wan 2.1 T2V 480p LoRA Ultra Fast — wavespeed-ai/wan-2.1/t2v-480p-lora-ultra-fast
Wan 2.1 T2V 480p LoRA Ultra Fast is a low-latency text-to-video model designed for rapid iteration. It generates short 480p clips from a single prompt, and supports adding LoRAs to steer style, characters, or motion patterns while keeping throughput high.
Key capabilities
- Text-to-video generation at 480p
- Ultra-fast inference for quick previews and batch exploration
- LoRA support for style/character control (up to 3 LoRAs per run)
- Prompt-driven motion, staging, and shot direction
- Works well for storyboard drafts, social content, and concept tests
Use cases
- Fast storyboard and pre-vis from a director-style prompt
- Stylized “template clips” using LoRAs (brand look, character identity, anime/toy/film looks)
- Social content ideation: generate 10–20 variations quickly, pick the best, upscale later
- LoRA-driven series: consistent visual language across multiple clips for campaigns
Pricing
| Output | Duration | Price per run | Effective price per second |
|---|---|---|---|
| 480p T2V (LoRA) | 5s | $0.125 | $0.025/s |
| 480p T2V (LoRA) | 10s | $0.188 | $0.0188/s |
Inputs
-
prompt (required): describe subject, action, scene, camera, and style
-
negative_prompt (optional): reduce blur, jitter, distortions, low-quality artifacts
-
loras (optional): up to 3 LoRAs, each with:
- path: owner/model-name or a direct .safetensors URL
- scale: LoRA strength (commonly around 0.6–1.0 to start)
Parameters
- duration: clip length (commonly 5s or 10s)
- size: output size preset (e.g., 832×480)
- num_inference_steps: more steps can improve stability/detail at the cost of speed
- guidance_scale: higher values follow the prompt more strongly (can reduce natural motion if too high)
- flow_shift: motion behavior tuning (useful for more/less dynamic motion)
- seed: set for reproducible results (-1 for random)
Prompting tips (T2V)
- Write like a shot list: subject + action + environment + camera + style
- Keep motion explicit: “slow pan left”, “subtle head turn”, “hands gesture while talking”
- For multi-panel or UI-like scenes (e.g., a video call), specify layout and per-panel actions clearly
- If using LoRAs, keep the base prompt simpler and let the LoRA carry most of the style signal