Imagen4
Playground
Try it on WavespeedAI!Imagen 4 is an AI image generator that produces detailed, high-quality images up to 2K across diverse styles and subjects. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Imagen 4 (Text-to-Image) — wavespeed-ai/imagen4
Imagen 4 is a high-quality text-to-image model for generating photorealistic and stylized images from prompts, with optional negative prompts for extra control. It’s well-suited for concept art, marketing creatives, portraits, and detailed scenes where you want clean composition and strong realism.
Key capabilities
- Text-to-image generation with strong realism and detail
- Optional negative_prompt to reduce unwanted artifacts or styles
- Reliable composition across common aspect ratios (e.g., 1:1, 16:9, 9:16)
- Supports multi-image output in a single run via num_images
Pricing
$0.04 per image.
Total cost = num_images × $0.04 Example: num_images = 4 → $0.16
How to use
- Write a prompt describing subject, setting, lighting, and style.
- Optionally add a negative_prompt listing what you want to avoid.
- Select aspect_ratio for your target layout.
- Choose num_images for how many variations you want.
- Set seed for reproducible results (optional), then generate.
Parameters
- prompt (required): The text description of what to generate
- negative_prompt (optional): What to avoid (artifacts, styles, objects, text, etc.)
- aspect_ratio: Output aspect ratio (e.g., 1:1, 16:9, 9:16)
- num_images: Number of images to generate per run
- seed: Fixed value for reproducibility; leave empty/random for variation
Prompting guide
A stable structure:
- Subject: who/what is in frame
- Scene: where + time + atmosphere
- Details: clothing, materials, environment cues
- Lighting: softbox, sunset, harsh noon, rim light
- Camera: close-up, wide shot, depth of field
- Style: photorealistic, cinematic, illustration, etc.
Example pattern: A [shot type] of [subject] in [scene]. [Lighting + mood]. [Camera cues]. [Style cues].
Example prompts
- A raw, unflinching photograph of a weathered soldier in a desert trench, dust blowing across his helmet and gear, harsh sunlight, shallow depth of field, cinematic realism.
- Studio product photo of a minimalist watch on a matte surface, softbox lighting, crisp shadow, premium advertising look.
- Cozy café interior at night, warm tungsten lighting, rain on windows, film still composition, subtle grain.
Negative prompt examples
- blurry, low resolution, deformed hands, extra fingers, bad anatomy
- watermark, logo, text, caption, jpeg artifacts
- oversaturated, cartoonish, plastic skin, uncanny face
Best practices
- Use negative_prompt sparingly; focus your main prompt on what you want.
- Keep the first sentence concrete, then add camera/lighting constraints.
- Fix seed when iterating on prompt wording for controlled comparisons.
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/imagen4" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"aspect_ratio": "1:1",
"num_images": 1
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${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. | |
| aspect_ratio | string | No | 1:1 | 1:1, 16:9, 9:16, 3:4, 4:3 | The aspect ratio of the generated media. |
| num_images | integer | No | 1 | 1 ~ 4 | The number of images to generate. |
| seed | integer | No | - | -1 ~ 2147483647 | The random seed to use for the generation. |
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 |