Wan 2.2 T2V 480p LoRA Ultra Fast
Playground
Try it 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.
Features
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.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/t2v-480p-lora-ultra-fast" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"size": "832*480",
"duration": 5,
"seed": -1
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| negative_prompt | string | No | - | The negative prompt for the generation. | |
| size | string | No | 832*480 | 832*480, 480*832 | The size of the generated media in pixels (width*height). |
| duration | integer | No | 5 | 5, 8 | The duration of the generated media in seconds. |
| loras | array | No | max 3 items | List of LoRAs to apply (max 3). | |
| loras[].path | string | Yes | - | Path to the LoRA model | |
| loras[].scale | float | Yes | - | 0.0 ~ 4.0 | Scale of the LoRA model |
| high_noise_loras | array | No | - | - | List of high noise LoRAs to apply (max 3). |
| low_noise_loras | array | No | - | - | List of low noise LoRAs to apply (max 3). |
| seed | integer | No | -1 | -1 ~ 2147483647 | The random seed to use for the generation. -1 means a random seed will be used. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Array of URLs to the generated content (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
| data.model | string | Model ID used for the prediction |
| data.outputs | string | Array of URLs to the generated content (empty when status is not completed). |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |