Dreamina V3.1 is a text-to-image model with enhanced aesthetics and style accuracy, producing richer, more polished images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.027per run·~37 / $1

A painter working in a sunlit studio, large canvas filled with abstract colors, brushes and paint tubes scattered on the floor, creative atmosphere.

An action shot of a male trail runner ascending a mountain ridge path at sunset. He is covered in dirt and sweat, his expression is determined, and his breath is visible in the cool air. The golden sunset light comes from behind, creating a strong rim light on his muscular silhouette. The background is rolling mountains and a spectacular sky.

Wide-angle view of a bustling night market, colorful lanterns hanging above, smoke rising from food stalls, people moving in blurred motion.

A candid portrait of an elderly woman sitting by a window, soft daylight on her face, hands gently holding a teacup, timeless and emotional feel.

A rainy evening in New York, yellow taxis reflecting on wet asphalt, a woman crossing the street with an umbrella, cinematic street photography style.

A young backpacker standing on top of a cliff in Santorini, overlooking whitewashed houses with blue domes, bright Mediterranean sunlight and deep blue sea.

A train passing through snowy mountains, smoke rising from the engine, pine trees covered in snow, cinematic winter travel scene.

A ferris wheel glowing at a seaside carnival, long exposure shot capturing colorful light trails against the dark sky.

A couple sitting on a rooftop under the night sky, city lights glowing below, Milky Way faintly visible above, romantic cinematic mood.
Generate beautiful, detailed images from text descriptions with latest Dreamina v3.1 model. Featuring flexible custom dimensions, enhanced prompt understanding, and high-fidelity output — perfect for creating professional visuals at an affordable price.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate. |
| size | No | Custom dimensions with separate width and height controls. |
| width | No | Output width in pixels (e.g., 1328). |
| height | No | Output height in pixels (e.g., 1328). |
| seed | No | Random seed for reproducibility. Use -1 for random. |
| enable_prompt_expansion | No | API only: Waits for image generation and returns it directly in the response. |
Flat rate per image generation.
| Output | Cost |
|---|---|
| Per image | $0.027 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bytedance/dreamina-v3.1/text-to-image 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 Dreamina v3.1 Text To Image below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/bytedance/dreamina-v3.1/text-to-image" \
-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": "1328*1328",
"seed": -1,
"enable_prompt_expansion": true,
"enable_base64_output": false,
"enable_sync_mode": false
}'
# 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].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("bytedance/dreamina-v3.1/text-to-image", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1328*1328",
"seed": -1,
"enable_prompt_expansion": true,
"enable_base64_output": false,
"enable_sync_mode": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"bytedance/dreamina-v3.1/text-to-image",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1328*1328",
"seed": -1,
"enable_prompt_expansion": true,
"enable_base64_output": false,
"enable_sync_mode": false
}
)
print(output["outputs"][0]) # → URL of the generated outputDreamina v3.1 Text To Image is a ByteDance model for image generation, exposed as a REST API on WaveSpeedAI. Dreamina V3.1 is a text-to-image model with enhanced aesthetics and style accuracy, producing richer, more polished images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
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/bytedance/bytedance-dreamina-v3.1-text-to-image.
Dreamina v3.1 Text To Image starts at $0.027 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.
Key inputs: `prompt`, `size`, `seed`, `enable_base64_output`, `enable_prompt_expansion`, `enable_sync_mode`. 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/bytedance/bytedance-dreamina-v3.1-text-to-image.
Average end-to-end generation time on WaveSpeedAI is around 27 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (ByteDance). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.