Qwen-Image-2512 LoRA is an enhanced 20B MMDiT text-to-image model with LoRA support for fast customization and refined image generation. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Ocioso

$0.025por execução·~40 / $1

three people in black suits floating above the grassy ground, looking down at each other from different angles, seen through a circular hole in the top of a green lawn, with a blue sky and a symmetrical composition, captured with a fisheye lens in high resolution, resulting in a hyper-realistic, cinematic photographic style reminiscent of kodak film stock.
Qwen Image 2512 LoRA is an enhanced version of the 20B MMDiT text-to-image model with LoRA support for fine-tuned control over style, characters, or artistic domains. Combine world-class text rendering with personalized generation through custom LoRA weights.
LoRA integration Import external.safetensors LoRA weights and control blending strength via scale parameter. Stack up to 3 LoRAs for hybrid results.
Superior text rendering Rivals GPT-4o in English and is best-in-class for Chinese typography. Text is seamlessly integrated into images, not overlaid.
Bilingual support Handles Chinese and English with diverse fonts and complex layouts.
Style versatility Photorealistic, anime, impressionist, or minimalist styles — all supported with consistent quality.
Reproducible results Lock the seed to maintain subject consistency when experimenting with different LoRAs.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Describe the image you want to create |
| width | No | Image width in pixels (up to 1536) |
| height | No | Image height in pixels (up to 1536) |
| lora_path | No | LoRA path (owner/model-name) or external.safetensors URL |
| lora_scale | No | LoRA strength (default: 1.0) |
| seed | No | Random seed for reproducible results (-1 for random) |
| output_format | No | Output format: jpeg, png, or webp |
| Item | Cost |
|---|---|
| Per image | $0.025 |
Simple flat-rate pricing regardless of image size or LoRA count.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/text-to-image-2512-lora 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 Qwen Image Text To Image 2512 Lora below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/text-to-image-2512-lora" \
-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",
"seed": -1,
"output_format": "jpeg",
"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("wavespeed-ai/qwen-image/text-to-image-2512-lora", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"seed": -1,
"output_format": "jpeg",
"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(
"wavespeed-ai/qwen-image/text-to-image-2512-lora",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "1024*1024",
"seed": -1,
"output_format": "jpeg",
"enable_sync_mode": false,
"enable_base64_output": false
}
)
print(output["outputs"][0]) # → URL of the generated outputQwen Image Text To Image 2512 Lora is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Qwen-Image-2512 LoRA is an enhanced 20B MMDiT text-to-image model with LoRA support for fast customization and refined image generation. 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/wavespeed-ai/qwen-image-text-to-image-2512-lora.
Qwen Image Text To Image 2512 Lora starts at $0.025 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_sync_mode`, `loras`. 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/wavespeed-ai/qwen-image-text-to-image-2512-lora.
Average end-to-end generation time on WaveSpeedAI is around 9 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 (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.