Stable Diffusion 3.5 Large Turbo produces high-res, fine-detailed text-to-image images in diverse styles with fewer inference steps. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
待機中

$0.041回あたり·~25 / $1

A young female mage with waist-length silver hair, speckled with tiny, glittering stars. She wears a deep blue velvet robe embroidered with golden moon phases and constellations. In her hand, she holds a staff made of white crystal, its tip levitating a small, softly glowing nebula. The background is an ancient library with towering bookshelves filled with magical tomes, and light filtering through stained-glass windows. --anime

A Viking longship with a dragon head prow, breaking through the waves in a mist-filled Norwegian fjord at dawn. The ship is filled with Viking warriors clad in furs, holding axes and shields, their expressions resolute. The dragon head on the bow is intricately carved, with a fearsome glare. Surrounded by steep cliffs and cascading waterfalls. The color palette is cool and stark, filled with an epic sense of history and adventure, realistic style with attention to historical detail. --ar 21:9

The moment of collision, blending, and explosion of multiple colored inks in water. Deep blues, vibrant magentas, and liquid-gold colors intertwine, forming complex, nebula-like organic shapes. Captured with high-speed photography, extremely sharp details, against a pure black background to emphasize the dynamic and unpredictable beauty of the colors. Abstract art, 4K resolution. --ar 16:9

An elderly artisan repairing a chair outside his workshop in an old Italian alley. He wears reading glasses on his wrinkled face, his expression focused. The afternoon sun casts strong light and shadows across him. Documentary photography style, black and white, high contrast, grainy texture, capturing a candid moment of real life. --style raw --ar 3:2

The busy Shibuya Crossing in Tokyo on a rainy night. Pedestrians hurry by with colorful umbrellas, the ground reflecting the blurred glow of neon signs and car lights. Street photography style, handheld camera perspective with slight motion blur, focused on a solitary figure from behind amidst the crowd. The photo is filled with a sense of urban dynamism and alienation. --ar 16:9

A stylishly dressed model wearing a unique piece of clothing from a Singaporean designer, posing against a backdrop of colorful Peranakan architecture in Joo Chiat. Soft, flattering light highlighting the details and design of the garment. Convey a sense of local culture and contemporary style. --ar 9:16

A male character leaning against a wall covered in neon graffiti. He has sharp black hair, and one of his eyes is covered by a high-tech eyepatch glowing with a faint red light. He wears a black trench coat with futuristic designs, and the seams of a cybernetic arm are visible. He grips the hilt of a high-frequency katana, his gaze cold and intense. The background is a rainy, futuristic city at night, the wet streets reflecting the vibrant lights of advertisements. --ar 9:16 --style raw

A female elf knight wearing lightweight armor crafted from leaves and white metal, with glowing vines wrapped around it. She has long golden hair woven into intricate braids and long, elegant pointed ears. She holds a longbow inlaid with a green gemstone, her expression firm and serene. She stands beneath a giant, bioluminescent ancient tree, surrounded by dancing fireflies. --ar 3:4
Generate high-fidelity images at turbo speed with Stability AI's most capable fast model. Stable Diffusion 3.5 Large Turbo combines the power of the Large architecture with optimized inference for rapid, detailed image generation from text prompts.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate. |
| image | No | Optional reference image for image-to-image generation (upload or URL). |
| aspect_ratio | No | Output aspect ratio (e.g., 16:9, 1:1, 9:16). Default: 16:9. |
| seed | No | Random seed for reproducibility. Use -1 for random. |
| enable_base64_output | No | API only: Returns base64 string instead of URL. |
Flat rate per image generation.
| Output | Cost |
|---|---|
| Per image | $0.04 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/stability-ai/stable-diffusion-3.5-large-turbo 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 Stable Diffusion 3.5 Large Turbo below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/stability-ai/stable-diffusion-3.5-large-turbo" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"aspect_ratio": "1:1",
"seed": -1,
"enable_base64_output": 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("stability-ai/stable-diffusion-3.5-large-turbo", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"aspect_ratio": "1:1",
"seed": -1,
"enable_base64_output": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"stability-ai/stable-diffusion-3.5-large-turbo",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"aspect_ratio": "1:1",
"seed": -1,
"enable_base64_output": false
}
)
print(output["outputs"][0]) # → URL of the generated outputStable Diffusion 3.5 Large Turbo is a Stability AI model for image generation, exposed as a REST API on WaveSpeedAI. Stable Diffusion 3.5 Large Turbo produces high-res, fine-detailed text-to-image images in diverse styles with fewer inference steps. 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/stability-ai/stability-ai-stable-diffusion-3.5-large-turbo.
Stable Diffusion 3.5 Large Turbo starts at $0.040 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`, `image`, `aspect_ratio`, `seed`, `enable_base64_output`. 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/stability-ai/stability-ai-stable-diffusion-3.5-large-turbo.
Average end-to-end generation time on WaveSpeedAI is around 3 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 (Stability AI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.