Bytedance Dreamina V3.0 Edit
Playground
Try it on WavespeedAI!ByteDance Dreamina 3.0 Edit is an image-to-image model that enhances aesthetics, style and detail and accepts text prompts. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
ByteDance Dreamina v3.0 Edit
Edit images with natural language instructions using ByteDance’s Dreamina v3.0 Edit model. Simply describe what you want to change — modify text, swap elements, adjust styles, or transform details — and watch the AI make precise, context-aware edits while preserving the rest of your image.
Why It Looks Great
- Natural language editing: Describe changes in plain text — no masks or complex tools required.
- Context-aware modifications: Understands image structure and makes edits that blend naturally.
- Text editing support: Change, replace, or modify text within images accurately.
- Custom output dimensions: Control the final image size with flexible width and height settings.
- Prompt Enhancer: Built-in tool to refine your editing instructions automatically.
- Reproducible results: Use the seed parameter to recreate exact outputs or explore variations.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text instruction describing the edit you want to make. |
| image | Yes | Source image to edit (upload or public URL). |
| size | No | Custom output dimensions with width and height controls. |
| width | No | Output width in pixels (e.g., 1024). |
| height | No | Output height in pixels (e.g., 1024). |
| seed | No | Random seed for reproducibility. Use -1 for random. |
How to Use
- Write your edit instruction — describe what you want to change in the image.
- Use Prompt Enhancer (optional) — click to refine your editing instruction.
- Upload your image — drag and drop or paste a public URL.
- Set dimensions (optional) — adjust width and height for the output size.
- Set seed (optional) — use -1 for random, or a specific number to reproduce results.
- Run — click the button to apply the edit.
- Download — preview and save your edited image.
Pricing
Flat rate per edit.
| Output | Cost |
|---|---|
| Per image | $0.027 |
Best Use Cases
- Text Replacement — Change text on clothing, signs, labels, or any surface in images.
- Element Modification — Swap colors, patterns, or specific objects within a scene.
- Style Adjustments — Modify lighting, mood, or visual style of existing images.
- Product Customization — Create variations of product images with different details.
- Content Localization — Adapt images for different markets by changing text or elements.
Example Prompts
- “Change the text on the girl’s clothes to Dreamina-v3.0”
- “Replace the logo on the cap with a star symbol”
- “Change the wall color from white to light blue”
- “Make the sky look like sunset with orange and pink colors”
- “Change the coffee cup to a tea cup”
- “Replace the text on the sign to say ‘Welcome Home‘“
Pro Tips for Best Results
- Be specific about what to change and what the result should be.
- Reference the element you want to edit clearly — “the text on the shirt”, “the logo on the cap”.
- For text changes, specify the exact new text you want.
- Keep output dimensions similar to the source for best quality preservation.
- Use the Prompt Enhancer to add clarity to simple instructions.
- The model preserves unchanged areas — focus your prompt only on what needs editing.
Notes
- If using a URL for the image, ensure it is publicly accessible. A preview thumbnail confirms successful loading.
- Complex edits may require more specific prompts for accurate results.
- The model works best when the edit target is clearly visible and identifiable in the image.
- For multiple edits, consider processing sequentially for better control.
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/bytedance/dreamina-v3.0/edit" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"size": "1328*1328",
"seed": -1,
"enable_base64_output": false,
"enable_sync_mode": false
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${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. | |
| image | string | Yes | - | The image to edit, can be a URL or base64 encoded image. | |
| size | string | No | 1328*1328 | 512 ~ 2048 per dimension | The size of the generated media in pixels (width*height). |
| seed | integer | No | -1 | -1 ~ 2147483647 | The random seed to use for the generation. -1 means a random seed will be used. |
| enable_base64_output | boolean | No | false | - | If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API. |
| enable_sync_mode | boolean | No | false | - | If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API. |
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 |