Ultra-fast Wan 2.2 text-to-video model producing 480p videos with custom LoRA support—generate unlimited AI videos with personalized styles. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.1per run·~10 / $1
ExamplesView all
A stunt motorcyclist launches off a ramp as two cars explode beneath him, flames and debris bursting into the air, bike chrome catching the orange glow, heat distortion visible, jacket fluttering wildly, cinematic motion blur realism
A young man rides his bicycle through a quiet city street at night, wind ruffling his shirt. Passing headlights create flares in the lens, and streetlights cast long shadows. Slow-motion cut as he pedals uphill, then a rear tracking shot from low angle.
Extreme close-up as a boxing glove lands on a focus pad. The camera captures skin ripple, sound impact in sync with vibration. Drops of sweat fly off, face partially seen in background, muscles contract sharply. High frame rate, cinematic grading, everything slows during the hit.
A track athlete crouches at the starting line, breath visible in the cold morning air. As the starting shot fires, he bursts forward, dirt and dust spraying behind him. The camera tracks low beside him, shoes pounding the track rhythmically, sun rising in golden glow.
A snowboarder speeds down a powder-covered slope, carving hard, snow exploding in arcs behind. The camera follows just above shoulder, capturing twists and jumps. GoPro-style quick spins, lens smudged with snow, sun flares through the trees.
Two cyberpunk bounty hunters exchanging gunfire in a narrow neon alley, rain pouring, puddles reflecting muzzle flashes
A lone swordsman standing in the middle of a burning bridge, sparks and ash swirling in the air, dramatic backlight
A lone special forces soldier sliding under gunfire in a war-torn city, muzzle flash illuminating dust in the air, cinematic lighting, ultra realistic, 4K
A battle-hardened special forces soldier dashes across a war-torn street under heavy gunfire, explosions lighting the ruined buildings behind him, dust and concrete shards flying with each step, sweat and grime covering his face, ultra cinematic lighting, photorealistic details
An archer stands on a snowy cliff edge in a raging blizzard, drawing his bow against the wind, frost clinging to his armor, snow swirling violently around, distant mountains fading into white mist, cinematic cold lighting and ultra sharp detail
Related Models
README
Wan 2.2 Text-to-Video 480p LoRA Ultra Fast
Generate customized videos from text prompts with LoRA support using Wan 2.2 Ultra Fast. This budget-friendly model creates 480p videos at blazing speed while allowing you to apply custom LoRA adapters — perfect for rapid prototyping, style testing, and high-volume content creation.
Looking for higher resolution? Try Wan 2.2 I2V 720p LoRA Ultra Fast for HD output.
Why It Looks Great
- Pure text-to-video: Generate videos from descriptions alone — no source images needed.
- LoRA support: Apply up to 3 custom LoRAs each for standard, high-noise, and low-noise stages.
- Ultra-fast generation: Optimized for maximum speed at the most affordable price.
- 480p output: Efficient resolution ideal for previews, social media, and rapid iteration.
- Negative prompt support: Exclude unwanted elements for precise control.
- Prompt Enhancer: Built-in tool to refine your descriptions automatically.
- Safety Checker: Optional content filtering for appropriate output.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the scene, motion, and action you want. |
| negative_prompt | No | Elements to avoid in the generated video. |
| duration | No | Video length: 5 or 8 seconds. Default: 5. |
| loras | No | Standard LoRA adapters to apply (up to 3). |
| high_noise_loras | No | LoRAs applied during high-noise denoising stages (up to 3). |
| low_noise_loras | No | LoRAs applied during low-noise denoising stages (up to 3). |
| seed | No | Random seed for reproducibility. Use -1 for random. |
| Enable Safety Checker | No | Toggle content safety filtering. |
How to Use
- Write your prompt — describe the scene, characters, motion, and style in detail.
- Use Prompt Enhancer (optional) — click to enrich your description.
- Add negative prompt (optional) — specify elements to exclude.
- Set duration — choose 5 or 8 seconds.
- Add LoRAs (optional) — click "+ Add Item" to include custom LoRA adapters.
- Set seed (optional) — for reproducible results.
- Run — click the button to generate.
- Download — preview and save your video.
Pricing
Per 5-second billing based on duration.
| Duration | Calculation | Cost |
|---|---|---|
| 5 seconds | 5 ÷ 5 × $0.10 | $0.10 |
| 8 seconds | 8 ÷ 5 × $0.10 | $0.16 |
Volume Examples
| Videos | Duration | Total Cost |
|---|---|---|
| 10 | 5s | $1.00 |
| 10 | 8s | $1.60 |
| 100 | 5s | $10.00 |
| 100 | 8s | $16.00 |
Understanding LoRA Options
This model provides three different LoRA slots that affect different stages of the generation process:
| LoRA Type | When Applied | Best For | Max Count |
|---|---|---|---|
| loras | Throughout generation | General style, character consistency | 3 |
| high_noise_loras | Early denoising (high noise) | Overall composition, major style elements | 3 |
| low_noise_loras | Late denoising (low noise) | Fine details, textures, finishing touches | 3 |
LoRA Strategy Tips
- Single style: Use standard
lorasfor consistent style throughout. - Layered control: Combine high_noise for composition + low_noise for details.
- Character + Style: Use one slot for character LoRA, another for style LoRA.
Best Use Cases
- Rapid Prototyping — Test concepts and LoRA combinations quickly before upgrading to HD.
- Style Exploration — Experiment with different LoRA styles at minimal cost.
- High-Volume Production — Generate large batches of content affordably.
- Social Media Previews — 480p works well for mobile-first platforms and stories.
- LoRA Testing — Iterate on LoRA combinations to find the perfect mix.
Example Prompts
- "A mystical forest at twilight, fireflies dancing between ancient trees, soft magical glow, fantasy atmosphere"
- "Futuristic cityscape with flying cars, neon lights reflecting on wet streets, cyberpunk aesthetic"
- "Ocean waves crashing on rocky shore, dramatic sunset sky, cinematic slow motion"
- "Character walking through cherry blossom garden, petals falling gently, anime style"
- "Abstract geometric shapes morphing and flowing, vibrant colors, hypnotic motion"
Pro Tips for Best Results
- Use 480p for testing, then regenerate favorites at 720p or higher for final delivery.
- Start without LoRAs to establish a baseline, then add them incrementally.
- Use high_noise_loras for major style changes, low_noise_loras for subtle refinements.
- Don't overload with LoRAs — sometimes 1-2 well-chosen LoRAs work better than many.
- Match your prompt language to the LoRA's training — use trigger words if applicable.
- 480p is perfect for vertical content on mobile platforms where resolution matters less.
How to Use LoRAs
For detailed guides on using and training custom LoRAs:
Resolution Comparison
| Model | Resolution | Cost (5s) | Best For |
|---|---|---|---|
| T2V 480p LoRA Ultra Fast | 480p | $0.10 | Testing, prototyping, high-volume |
| I2V 720p LoRA Ultra Fast | 720p | $0.15 | Final delivery, quality content |
Notes
- Each LoRA slot (loras, high_noise_loras, low_noise_loras) supports up to 3 LoRAs.
- LoRA effects are cumulative — adding more LoRAs increases their combined influence.
- Enable Safety Checker for content that will be publicly shared.
- Processing is extremely fast — ideal for rapid iteration workflows.
- 480p is sufficient for most mobile viewing and social media platforms.
Wan 2.2 T2v 480p Lora Ultra Fast API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/t2v-480p-lora-ultra-fast with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read URLs from data.outputs. Examples for Wan 2.2 T2v 480p Lora Ultra Fast below.
HTTP example
# Submit the prediction
curl --fail-with-body --connect-timeout 10 --max-time 60 \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/t2v-480p-lora-ultra-fast" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"duration": 5,
"seed": -1
}'
# Wait at least 2 seconds, then poll. Safe GET requests may be retried.
curl --fail-with-body --connect-timeout 10 --max-time 30 \
--retry 4 --retry-all-errors --retry-delay 1 \
-X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# Start at 2 seconds and increase the interval for long-running tasks.
# Stop on completed, failed, cancelled, or timeout.Node.js example
// npm install wavespeed
const { Client } = require('wavespeed');
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
const client = new Client(apiKey);
try {
const result = await client.run("wavespeed-ai/wan-2.2/t2v-480p-lora-ultra-fast", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"duration": 5,
"seed": -1
}, {
timeout: 3600,
pollInterval: 2.0,
});
console.log(result.outputs);
} catch (error) {
console.error('Generation failed:', error);
process.exitCode = 1;
}Python example
# pip install wavespeed
import os
from wavespeed import Client
client = Client(api_key=os.environ["WAVESPEED_API_KEY"])
try:
output = client.run(
"wavespeed-ai/wan-2.2/t2v-480p-lora-ultra-fast",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"duration": 5,
"seed": -1
},
timeout=3600.0,
poll_interval=2.0,
)
print(output["outputs"])
except Exception as error:
raise SystemExit(f"Generation failed: {error}") from errorWan 2.2 T2v 480p Lora Ultra Fast API — Frequently asked questions
What is the Wan 2.2 T2v 480p Lora Ultra Fast API?
Wan 2.2 T2v 480p Lora Ultra Fast is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Ultra-fast Wan 2.2 text-to-video model producing 480p videos with custom LoRA support—generate unlimited AI videos with 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 2.2 T2v 480p Lora Ultra Fast 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/wan-2.2-t2v-480p-lora-ultra-fast.
How much does Wan 2.2 T2v 480p Lora Ultra Fast cost per run?
Wan 2.2 T2v 480p Lora Ultra Fast starts at $0.10 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 2.2 T2v 480p Lora Ultra Fast accept?
Key inputs: `prompt`, `duration`, `size`, `seed`, `negative_prompt`, `high_noise_loras`. 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-2.2-t2v-480p-lora-ultra-fast.
How long does Wan 2.2 T2v 480p Lora Ultra Fast take to generate?
Average end-to-end generation time on WaveSpeedAI is around 42 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 2.2 T2v 480p Lora Ultra Fast 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.