Wan 2.1 T2V 480p LoRA Ultra Fast

Wan 2.1 T2V 480p LoRA Ultra Fast

Playground

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.

Features

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

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

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/t2v-480p-lora-ultra-fast" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "loras": [
        {
            "path": "Remade-AI/Zoom-Call",
            "scale": 1
        }
    ],
    "size": "832*480",
    "num_inference_steps": 30,
    "duration": 5,
    "guidance_scale": 5,
    "flow_shift": 3,
    "seed": -1
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"