Wan 2.1 T2V 720P LoRA | Custom LoRA Image API

Wan 2.1 Text-to-Video 720p LoRA

Generate stunning videos from text descriptions with Wan 2.1 Text-to-Video 720p LoRA. This powerful model transforms your written prompts into high-quality 720p videos with smooth motion and cinematic quality — plus full LoRA support for custom styles, characters, and aesthetics.

Why It Stands Out

Pure text-to-video generation: No source image needed — describe your vision and watch it come to life.
LoRA support: Load custom LoRA models to apply specific styles, maintain character consistency, or match brand aesthetics.
Prompt-guided creation: Control scenes, actions, camera movements, and atmosphere through natural language.
Negative prompt support: Exclude unwanted elements for cleaner, more controlled outputs.
Flexible duration: Generate 5-second or 10-second clips depending on your needs.
Reproducibility: Use the seed parameter to recreate exact results or iterate on variations.

Pricing

Duration	Price
5 seconds	$0.30
10 seconds	$0.45

Parameters

Parameter	Required	Description
prompt	Yes	Text description of the video you want to generate.
negative_prompt	No	Elements to avoid in the generated video.
lora_url	No	URL to your custom LoRA model file.
lora_strength	No	LoRA influence strength (typically 0.5–1.0).
size	No	Output resolution (default: 1280×720).
num_inference_steps	No	Quality/speed trade-off (default: 30).
duration	No	Video length in seconds: 5 or 10 (default: 5).
guidance_scale	No	Prompt adherence strength (default: 5).
flow_shift	No	Motion intensity control (default: 5).
seed	No	Set for reproducibility; -1 for random.

How to Use

Write a prompt describing the scene, action, and style you want.
Add a LoRA (optional) — paste the URL to your custom LoRA and set the strength.
Set parameters — adjust duration, guidance scale, and other settings as needed.
Add a negative prompt (optional) to exclude unwanted elements.
Click Run and wait for your video to generate.
Preview and download the result.

How to Use LoRA

LoRA (Low-Rank Adaptation) lets you customize the model's output style without retraining the full model.

Use your LoRA: Host your .safetensors file at a public URL and paste it into the lora_url field.
Train your LoRA: Learn how to create custom LoRAs in our guide: Train Your Own LoRA Model

Common LoRA use cases: consistent character appearance, specific art styles, brand-aligned aesthetics, anime/cartoon styles.

Best Use Cases

Social Media Content — Create scroll-stopping video content from scratch.
Marketing & Advertising — Produce concept videos and ad creatives without filming.
Storytelling & Animation — Generate scenes for short films, music videos, or narrative projects.
Game & App Development — Create promotional trailers and UI animations.
Personalized Content — Use custom LoRAs for branded or character-consistent videos.

Pro Tips for Best Quality

Be specific in your prompt — describe subject, action, environment, lighting, and camera movement.
Use negative prompts to reduce common artifacts: blur, distortion, jitter, or watermarks.
Start with lower inference steps (20–25) for quick previews, then increase for final renders.
When using LoRA, start with strength around 0.7 and adjust based on results.
Fix the seed when iterating to isolate the effect of parameter changes.

Notes

Ensure any LoRA URLs are publicly accessible.
Processing time varies based on duration and current queue load.
Please ensure your prompts comply with content guidelines.

Wan 2.1 T2v 720p Lora API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/t2v-720p-lora with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Wan 2.1 T2v 720p Lora below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/t2v-720p-lora" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "negative_prompt": "blurry, low quality, distorted",
    "loras": [
        {
            "path": "Remade-AI/Fire",
            "scale": 1
        }
    ],
    "size": "1280*720",
    "num_inference_steps": 30,
    "duration": 5,
    "guidance_scale": 5,
    "flow_shift": 5,
    "seed": -1
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("wavespeed-ai/wan-2.1/t2v-720p-lora", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "negative_prompt": "blurry, low quality, distorted",
        "loras": [
                {
                        "path": "Remade-AI/Fire",
                        "scale": 1
                }
        ],
        "size": "1280*720",
        "num_inference_steps": 30,
        "duration": 5,
        "guidance_scale": 5,
        "flow_shift": 5,
        "seed": -1
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "wavespeed-ai/wan-2.1/t2v-720p-lora",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "negative_prompt": "blurry, low quality, distorted",
    "loras": [
        {
            "path": "Remade-AI/Fire",
            "scale": 1
        }
    ],
    "size": "1280*720",
    "num_inference_steps": 30,
    "duration": 5,
    "guidance_scale": 5,
    "flow_shift": 5,
    "seed": -1
}
)

print(output["outputs"][0])  # → URL of the generated output

Wan 2.1 T2v 720p Lora API — Frequently asked questions

What is the Wan 2.1 T2v 720p Lora API?

Wan 2.1 T2v 720p Lora is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Wan 2.1 Text-to-Video 720P creates 720P videos from text prompts and supports custom LoRAs for personalized styles. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Wan 2.1 T2v 720p Lora API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/wan-2.1-t2v-720p-lora.

How much does Wan 2.1 T2v 720p Lora cost per run?

Wan 2.1 T2v 720p Lora starts at $0.30 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Wan 2.1 T2v 720p Lora accept?

Key inputs: `prompt`, `duration`, `size`, `seed`, `guidance_scale`, `num_inference_steps`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/wan-2.1-t2v-720p-lora.

How long does Wan 2.1 T2v 720p Lora take to generate?

Average end-to-end generation time on WaveSpeedAI is around 94 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Wan 2.1 T2v 720p Lora outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

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