Z-AI CogView-4 generates high-quality images from text prompts with a quick and accurate understanding of user descriptions, letting AI express images more precisely and personally. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Boşta

$0.01çalıştırma başına·~100 / $1

high-resolution collage of various mood board elements inspired by the aesthetics of Giò Ponti, beautiful designed and illustrated sardine tin cans, canned delicatesses, luxury delicatesses, white background, no shadows, hyper-realistic.

A hyper-realistic glass perfume bottle on a marble surface, dramatic hard light, crisp shadows, soft reflections, luxury product photography style.

Mediterranean food festival poster, vibrant colors, illustrations of seafood and spices, playful typography, sunny coastal theme. Words:" Mediterranean Food Festival. Come and enjoy!"
CogView-4 is Z.AI's high-quality text-to-image generation model designed to transform natural-language descriptions into precise, personalized visuals. It excels at interpreting user intent — producing images that accurately reflect your creative vision with strong compositional clarity and visual appeal.
Precise prompt understanding Accurately interprets detailed prompts to generate images that match your description — balancing subject, context, and style with strong fidelity.
Flexible quality modes Choose standard for fast results (5-10 seconds) or hd for richer detail and visual depth (~20 seconds).
Wide aspect ratio support Multiple presets from square to portrait, landscape, and ultra-wide formats for social, web, or print use.
Prompt Enhancer Built-in tool to automatically improve your prompts for better generation results.
Fast, reliable generation Optimized for quick turnaround with stable output quality — ideal for rapid ideation and creative iteration.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate |
| size | No | Output dimensions (default: 1024*1024) |
| quality | No | Rendering quality: standard or hd |
| Size | Orientation | Best For |
|---|---|---|
| 1024*1024 | Square | Social posts, avatars, album art |
| 768*1344 | Portrait | Mobile screens, stories, vertical banners |
| 864*1152 | Portrait | Mobile displays, vertical content |
| 1344*768 | Landscape | Web headers, presentations |
| 1152*864 | Landscape | Widescreen designs, banners |
| 1440*720 | Ultra-wide | Cinematic layouts, panoramic visuals |
| 720*1440 | Ultra-tall | Immersive vertical content |
| Item | Cost |
|---|---|
| Per image | $0.01 |
Simple flat-rate pricing regardless of size or quality settings.
Please ensure your prompts comply with content guidelines. If an error occurs, review your prompt and try again.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/z-ai/cogview-4 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 Cogview 4 below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/z-ai/cogview-4" \
-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": "1024*1024",
"quality": "hd",
"enable_sync_mode": false,
"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("z-ai/cogview-4", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"quality": "hd",
"enable_sync_mode": false,
"enable_base64_output": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"z-ai/cogview-4",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"quality": "hd",
"enable_sync_mode": false,
"enable_base64_output": false
}
)
print(output["outputs"][0]) # → URL of the generated outputCogview 4 is a Z Ai model for image generation, exposed as a REST API on WaveSpeedAI. Z-AI CogView-4 generates high-quality images from text prompts with a quick and accurate understanding of user descriptions, letting AI express images more precisely and personally. Ready-to-use REST inference API, best performance, no cold starts, 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/z-ai/z-ai-cogview-4.
Cogview 4 starts at $0.010 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`, `enable_base64_output`, `enable_sync_mode`, `quality`. 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/z-ai/z-ai-cogview-4.
Average end-to-end generation time on WaveSpeedAI is around 36 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 (Z Ai). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.