FLUX.1 [schnell] is a 12B-parameter rectified flow transformer that generates images from text prompts and supports LoRA adapters. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.005per run·~200 / $1
ExamplesView all
Super realism, ultra-realistic, a stylish woman sitting by a window, reading a book, sunlight streaming in, bright soft lighting, cozy modern interior, subtle skin texture, natural smile, casual elegance, lifestyle photography, crisp details, 85mm lens
Animated Siamese cat, candlelight, mysterious alley, cartoon style, warm glow
pikesi,Pixar style,1cat, beautify
Super Realism, Headshot of handsome young man, wearing dark gray sweater with buttons and big shawl collar, brown hair and short beard, serious look on his face, black background, soft studio lighting, portrait photography --ar 85:128 --v 6.0 --style rawHeadshot of handsome young man, wearing dark gray sweater with buttons and big shawl collar, brown hair and short beard, serious look on his face, black background, soft studio lighting, portrait photography --ar 85:128 --v 6.0 --style rawHeadshot of handsome young man, wearing dark gray sweater with buttons and big shawl collar, brown hair and short beard, serious look on his face, black background, soft studio lighting, portrait photography --ar 85:128 --v 6.0 --style raw
Super Realism, High-resolution photograph, woman, UHD, photorealistic, shot on a Sony A7III --chaos 20 --ar 1:2 --style raw --stylize 250
Super Realism, Woman in a red jacket, snowy, in the style of hyper-realistic portraiture, caninecore, mountainous vistas, timeless beauty, palewave, iconic, distinctive noses --ar 72:101 --stylize 750 --v 6
Related Models
README
FLUX.1 Schnell LoRA — wavespeed-ai/flux-schnell-lora
wavespeed-ai/flux-schnell-lora is a fast, high-throughput text-to-image model with LoRA support for style and identity control. Use it when you want Schnell-level speed, but also need consistent aesthetics across batches (brand looks, character styles, “same vibe” series).
Key capabilities
- LoRA-guided generation for consistent style, mood, or subject traits
- Ultra-fast iterations for prompt exploration and batch workflows
- Optional image + mask inputs for reference-based edits (when enabled)
- Up to 3 LoRAs per run (mix styles or add a single strong look)
Inputs
-
Prompt (required): text description of the image you want
-
Image (optional): reference image input (if available in your deployment)
-
Mask image (optional): mask for local edits / inpainting (if available)
-
Strength (optional): how strongly edits follow the image/mask intent
-
LoRAs (optional): up to 3 LoRA items, each with:
-
Path: LoRA identifier (for example, a LoRA repo/name)
-
Scale: LoRA weight/strength
-
Size: output width and height
-
Num images: number of images to generate
-
Seed: random seed for reproducibility
-
Output format: jpeg, png, etc.
-
Base64 output (API only): return base64 instead of a URL
-
Sync mode (API only): wait for the result before returning
Recommended usage patterns
- One-LoRA “signature look”: start with a single LoRA and moderate scale, then iterate prompts for composition and lighting.
- Style blending: combine 2 LoRAs (e.g., lighting + texture) and keep scales conservative to avoid overcooking details.
- Consistency runs: fix the seed, lock the LoRA set, then vary only one prompt element per iteration.
Use cases
- Brand creative at scale: generate a whole campaign’s visuals in one consistent style
- Character/style series: keep the same “feel” across thumbnails, posters, or profile sets
- Product mock concepts: explore layouts quickly while preserving a chosen aesthetic
- Rapid A/B exploration: batch variations under a stable LoRA look for easy comparison
- Creator workflows: build a repeatable visual identity without sacrificing speed
Pricing
| Model | Price per image | LoRA limit |
|---|---|---|
| wavespeed-ai/flux-schnell-lora | $0.005 | Up to 3 |
Flux Schnell Lora API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-schnell-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 Flux Schnell Lora below.
HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-schnell-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",
"image": "https://example.com/your-input.jpg",
"strength": 0.8,
"loras": [
{
"path": "strangerzonehf/Flux-Super-Realism-LoRA",
"scale": 1
}
],
"size": "1024*1024",
"num_images": 1,
"seed": -1,
"output_format": "jpeg",
"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].Node.js example
// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/flux-schnell-lora", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"strength": 0.8,
"loras": [
{
"path": "strangerzonehf/Flux-Super-Realism-LoRA",
"scale": 1
}
],
"size": "1024*1024",
"num_images": 1,
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
});
console.log(result.outputs[0]); // → URL of the generated outputPython example
# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/flux-schnell-lora",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"strength": 0.8,
"loras": [
{
"path": "strangerzonehf/Flux-Super-Realism-LoRA",
"scale": 1
}
],
"size": "1024*1024",
"num_images": 1,
"seed": -1,
"output_format": "jpeg",
"enable_base64_output": false,
"enable_sync_mode": false
}
)
print(output["outputs"][0]) # → URL of the generated outputFlux Schnell Lora API — Frequently asked questions
What is the Flux Schnell Lora API?
Flux Schnell Lora is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. FLUX.1 [schnell] is a 12B-parameter rectified flow transformer that generates images from text prompts and supports LoRA adapters. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
How do I call the Flux Schnell Lora API?
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/flux-schnell-lora.
How much does Flux Schnell Lora cost per run?
Flux Schnell Lora starts at $0.005 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.
What inputs does Flux Schnell Lora accept?
Key inputs: `prompt`, `image`, `size`, `seed`, `enable_base64_output`, `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/wavespeed-ai/flux-schnell-lora.
How long does Flux Schnell Lora take to generate?
Average end-to-end generation time on WaveSpeedAI is around 125 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Can I use Flux Schnell Lora outputs commercially?
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.