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lora-support

Flux Kontext Dev LoRA

wavespeed-ai/flux-kontext-dev-lora

Fast FLUX.1 Kontext [dev] endpoint with LoRA support for rapid image editing using pre-trained adapters for brand and style. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Input

Hint: You can drag and drop a file or click to upload

preview
width
height
1024 × 1024 px
Range: 256 - 1536
If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.
If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.

Idle

Replace 'Feel POWER' with 'WaveSpeedAI'

Sua solicitação custará $0.03 por execução.

Por $1 você pode executar este modelo aproximadamente 33 vezes.

ExemplosVer todos

a dog frstingln illustration
Replace 'Feel POWER' with 'WaveSpeedAI'
Transform the image into detailed anime style. Keep the original composition and layout, but render all characters with smooth outlines, large expressive eyes, vibrant hair colors, and soft cel-shading. Background should resemble high-quality anime scenes — painterly skies, stylized lighting, and subtle gradients. Make it feel like a frame from a cinematic anime.
Turn it into a lego style
Turning clothes into bikinis
change the car color to pink
v3ct0r style, simple flat vector art, isolated on white bg, Mona Lisa
v3ct0r style, simple flat vector art, isolated on white bg, a girl
Mona Lisa, blockprint style
A young man with sunglasses, portrait, blockprint style

README

FLUX Kontext Dev LoRA — wavespeed-ai/flux-kontext-dev-lora

FLUX Kontext Dev LoRA is an instruction-based image-to-image editing model with built-in LoRA support. Provide a source image plus a natural-language edit request, and optionally attach up to 3 LoRAs to steer style, subject consistency, or domain-specific aesthetics during the edit.

Key capabilities

  • Image-to-image editing from a source image + text instruction
  • LoRA-enabled inference: apply up to 3 LoRAs via input parameters
  • Works for both local edits (specific changes) and global transforms (overall look)
  • Ideal for batch consistency: reuse the same LoRA set for a stable visual identity

Pricing

$0.03 per image.

Cost per run = num_images × $0.03 Example: num_images = 4 → $0.12

Inputs and outputs

Input:

  • One source image (upload or public URL)
  • One edit instruction (prompt)
  • Optional: up to 3 LoRA items

Output:

  • One or more edited images (controlled by num_images)

Parameters

Core:

  • prompt: Edit instruction describing what to change and what to preserve
  • image: Source image
  • width / height: Output resolution
  • num_inference_steps: More steps can improve fidelity but increases latency
  • guidance_scale: Higher values follow the prompt more strongly; too high may over-edit
  • num_images: Number of variations generated per run
  • seed: Fixed value for reproducibility; -1 for random
  • output_format: jpeg or png

LoRA (up to 3 items):

  • loras: A list of LoRA entries (max 3)

    • path: Either owner/model-name or a direct .safetensors URL from the Internet
    • scale: LoRA strength (typically start around 0.6–1.0 and adjust)

Prompting guide

Use “preserve + edit + constraints” and let LoRAs drive the look:

Template: Keep [what must stay]. Change [what to edit]. Ensure [constraints]. Apply the LoRA style consistently without changing identity.

Example prompts

  • Keep the person’s face, hairstyle, and pose unchanged. Replace the background with a clean studio gradient. Match lighting and shadows.
  • Keep the product shape and label layout unchanged. Replace only the label text with “WaveSpeedAI”. Preserve typography perspective and print texture.
  • Remove small blemishes and reduce glare on the forehead while keeping natural skin texture and pores.

Best practices

  • Use fewer LoRAs when possible; add a second/third only if you need combined effects.
  • If results drift or over-style, reduce LoRA scale or guidance_scale and strengthen the preserve clause.
  • For consistent batches, keep the same LoRA set and scales, and fix seed when comparing prompt variants.