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Sdxl Lora API Pricing Comparison

The SDXL LoRA image model enhances Stable Diffusion XL with specialized fine-tuning, letting you generate images in unique styles, characters, or themes. By applying LoRA weights, you can create visuals that match a specific aesthetic, celebrity look, anime style, or custom-trained subject.

Savings Alert33% ↓Cheaper than Fal.ai

Model Overview

The SDXL LoRA image model is a cutting-edge enhancement for Stable Diffusion XL, meticulously optimized through specialized fine-tuning. By applying domain-specific LoRA weights, this model not only adapts to unique aesthetics and thematic styles but also delivers consistently high-quality visuals, making it a versatile tool for artists, designers, and developers. Its underlying technology leverages advanced machine learning techniques and the powerful capabilities of Stable Diffusion XL, resulting in a model that excels in generating images that resonate with detailed, custom styles. Designed for both technical experts and creative users, the SDXL LoRA image model stands out with its ability to incorporate diverse styles, including celebrity likeness, anime designs, or other custom-trained subjects. With an intuitive input schema, users can easily adjust parameters such as image dimensions and LoRA weight scales, ensuring a precise match to their creative vision. Whether for commercial artwork, digital storytelling, or innovative design experiments, this model offers a robust, flexible, and cost-effective solution for generating dynamic images.

Interactive Savings Calculator

Estimate monthly API spend and compare absolute developer savings.

Monthly API Generations10,000 runs
50025,00050,00075,000100,000+
MuAPI Monthly Cost

$20.00

$0.002 per generation
Fal.ai Cost

$30.00

$0.003 per generation
Estimated Monthly Savings$10.00
Annual Savings$120.00

Detailed Pricing Breakdown

ProviderEstimated RateNotes
muapiapp$0.002 per generationmuapiapp offers this model at a cost that is 20-50% more affordable than its competitors, without compromising on quality or performance.
Fal.ai$0.003 per generationWhile Fal.ai provides a similar service at almost identical quality, muapiapp is priced 20-50% lower, making it a superior value proposition.
Replicate$0.003 per generationReplicate offers comparable quality at a rate that is nearly identical to Fal.ai; however, muapiapp remains 20-50% more cost-efficient for users.

Developer Integration Snippets

1import requests 2import time 3import json 4 5api_key = "YOUR_API_KEY" 6url = "https://api.muapi.ai/workflow/run/sdxl-lora" 7 8def poll_for_result(run_id): 9 url = f"https://api.muapi.ai/workflow/run/{run_id}/api-outputs" 10 headers = { 11 "Content-Type": "application/json", 12 "x-api-key": f"{api_key}", 13 } 14 while True: 15 response = requests.get(url, headers=headers) 16 result = response.json() 17 18 if result['status'] == 'completed': 19 return json.loads(result['outputs']) 20 21 if result['status'] == 'failed': 22 raise Exception(result.get('error', 'Generation failed')) 23 24 time.sleep(5) 25 26data = { 27 "schemas": { 28 "input_data": { 29 "x-order-properties": [ 30 "prompt", 31 "width", 32 "height", 33 "lora_list" 34 ], 35 "type": "object", 36 "properties": { 37 "prompt": { 38 "examples": [ 39 "An elegant fantasy queen sitting on a crystal throne, shimmering crown, ethereal lighting, magical atmosphere." 40 ], 41 "description": "Text prompt describing the image.", 42 "type": "string", 43 "title": "Prompt", 44 "name": "prompt" 45 }, 46 "lora_list": { 47 "examples": [ 48 { 49 "path": "https://civitai.com/api/download/models/242686?type=Model&format=SafeTensor", 50 "scale": 1 51 } 52 ], 53 "title": "LoRA List", 54 "name": "lora_list", 55 "type": "array", 56 "items": { 57 "type": "object", 58 "properties": { 59 "path": { 60 "type": "string", 61 "format": "url", 62 "title": "Path", 63 "name": "path", 64 "description": "URL or the path to the LoRA weights." 65 }, 66 "scale": { 67 "type": "number", 68 "title": "Scale", 69 "name": "scale", 70 "description": "The scale of the LoRA weight. This is used to scale the LoRA weight before merging it with the base model. Default value: 1", 71 "minValue": 0, 72 "maxValue": 4, 73 "step": 0.01, 74 "default": 1 75 } 76 } 77 }, 78 "description": "The LoRA weights for generating video", 79 "maxItems": 4 80 }, 81 "width": { 82 "title": "Width", 83 "name": "width", 84 "type": "int", 85 "description": "Width of the output image.", 86 "default": 1024, 87 "minValue": 256, 88 "maxValue": 1536, 89 "step": 1, 90 "isEdit": true 91 }, 92 "height": { 93 "title": "Height", 94 "name": "height", 95 "type": "int", 96 "description": "Height of the output image.", 97 "default": 1024, 98 "minValue": 256, 99 "maxValue": 1536, 100 "step": 1, 101 "isEdit": true 102 } 103 }, 104 "title": "BaseInput", 105 "required": [ 106 "prompt" 107 ], 108 "endpoint_url": "sdxl-lora-image" 109 }, 110 "output_data": { 111 "x-fal-order-properties": [ 112 "image" 113 ], 114 "type": "object", 115 "properties": { 116 "video": { 117 "examples": [ 118 "https://d3adwkbyhxyrtq.cloudfront.net/ai-images/186/631019725223/586cb729-67f8-4f41-b6f4-7176a41c5adf.jpg" 119 ], 120 "description": "The generated image", 121 "title": "Image", 122 "comparison": false 123 } 124 }, 125 "title": "SdxlLoRA", 126 "required": [ 127 "image" 128 ] 129 } 130 } 131} 132 133headers = { 134 "Content-Type": "application/json", 135 "x-api-key": f"{api_key}", 136} 137 138response = requests.post(url, json=data, headers=headers) 139 140result = response.json() 141print("Queued:", result) 142 143outputs = poll_for_result(result["run_id"]) 144print("Completed:", outputs) 145

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