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Image to Video

Image to Video API Pricing

Animate any image by turning it into a video with motion effects or scene continuity. RunwayML’s I2V model transforms static visuals into short clips by extrapolating depth, movement, and temporal dynamics.

Savings Alert40% ↓Cheaper than Fal.ai

About Image to Video

Runway Image-to-Video is a cutting-edge AI model that transforms static images into dynamic videos by applying complex motion effects and scene continuity. By leveraging advanced algorithms that extrapolate depth, movement, and temporal dynamics, the model creates short, engaging clips from single visuals. This innovative approach allows users to explore new dimensions of visual storytelling, blending art and technology seamlessly. Built on the proprietary techniques of RunwayML, this model is highly optimized for efficiency and quality. Its user-friendly configuration, detailed prompt options, and customizable output settings (aspect ratio, resolution, and duration) provide both novices and professionals with a powerful tool for video generation. Whether used for marketing visuals, digital art projects, or creative storytelling, the model stands out as a high-performance solution in the evolving landscape of image-to-video technology.

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Estimate monthly API spend and compare absolute developer savings.

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

$1500.00

$0.15 per generation
Fal.ai Cost

$2500.00

$0.25 per generation
Estimated Monthly Savings$1000.00
Annual Savings$12000.00

Detailed Pricing Breakdown

ProviderEstimated RateNotes
muapiapp$0.15 per generationmuapiapp offers exceptional affordability, being 20-50% cheaper than key competitors while maintaining comparable or superior quality.
Fal.ai$0.25 per generationFal.ai's pricing is nearly identical to Replicate, but muapiapp provides a more cost-effective solution at 20-50% lower costs.
Replicate$0.26 per generationReplicate offers similar capabilities at a slightly higher price point. In comparison, muapiapp is 20-50% more affordable without compromising on quality.

Developer Integration Snippets

1import requests 2import time 3import json 4 5api_key = "YOUR_API_KEY" 6url = "https://api.muapi.ai/workflow/run/runway-image-to-video" 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 "image_url", 32 "aspect_ratio", 33 "resolution", 34 "duration" 35 ], 36 "type": "object", 37 "properties": { 38 "prompt": { 39 "examples": [ 40 "The camera smoothly zooms in on the sleek, futuristic race car as it speeds through a neon-lit urban tunnel at twilight, its glossy white surface reflecting the vibrant pink and blue lights streaking past. The precise detailing of the car’s aerodynamic curves and glowing accents is highlighted as droplets of water spray from the spinning tires, adding a palpable sense of motion and intensity. The driver’s black helmet, contrasted against the car’s gleaming body, remains sharply in focus, emphasizing the thrilling high-speed chase through the city. The blurred cityscape and illuminated digital billboards in the background create a high-tech, cyberpunk atmosphere, intensifying the scene’s adrenaline and futuristic vibe." 41 ], 42 "description": "The prompt to be used to generate a video", 43 "type": "string", 44 "title": "Prompt", 45 "name": "prompt" 46 }, 47 "image_url": { 48 "examples": [ 49 "https://d3adwkbyhxyrtq.cloudfront.net/ai-images/186/809475541516/a895607c-b724-427c-9020-6c36ebc4af25.jpg" 50 ], 51 "description": "URL of the input image. Provides visual reference for AI", 52 "field": "image", 53 "type": "string", 54 "title": "Image URL", 55 "name": "image_url" 56 }, 57 "aspect_ratio": { 58 "enum": [ 59 "16:9", 60 "9:16", 61 "1:1", 62 "4:3", 63 "3:4" 64 ], 65 "title": "Aspect Ratio", 66 "name": "aspect_ratio", 67 "type": "string", 68 "description": "Aspect ratio of the output video.", 69 "default": "16:9" 70 }, 71 "resolution": { 72 "enum": [ 73 "720p", 74 "1080p" 75 ], 76 "title": "Resolution", 77 "name": "resolution", 78 "type": "string", 79 "description": "The resolution of the generated video. If 1080p is selected, 8-second video cannot be generated.", 80 "default": "720p" 81 }, 82 "duration": { 83 "enum": [ 84 5, 85 8 86 ], 87 "title": "Duration", 88 "name": "duration", 89 "type": "int", 90 "description": "The duration in seconds. If 8-second video is selected, 1080p resolution cannot be used.", 91 "default": 5 92 } 93 }, 94 "title": "BaseInput", 95 "required": [ 96 "prompt", 97 "image_url" 98 ], 99 "endpoint_url": "runway-image-to-video" 100 }, 101 "output_data": { 102 "x-fal-order-properties": [ 103 "video" 104 ], 105 "type": "object", 106 "properties": { 107 "video": { 108 "examples": [ 109 "https://d3adwkbyhxyrtq.cloudfront.net/videos/186/183586710774/8d9fa8a2-19d7-4c7f-ae97-57ec7aca0370.mp4" 110 ], 111 "description": "The generated video", 112 "title": "Video", 113 "comparison": false 114 } 115 }, 116 "title": "RunwayI2VVideo", 117 "required": [ 118 "video" 119 ] 120 } 121 } 122} 123 124headers = { 125 "Content-Type": "application/json", 126 "x-api-key": f"{api_key}", 127} 128 129response = requests.post(url, json=data, headers=headers) 130 131result = response.json() 132print("Queued:", result) 133 134outputs = poll_for_result(result["run_id"]) 135print("Completed:", outputs) 136

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