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AWS Rekognition charges per image analysed. Running YOLOv8 on a dedicated GPU server from GigaGPU processes unlimited images for a fixed monthly cost. For security camera feeds, quality inspection systems, or any application running real-time object detection, the cost difference at scale is massive.
YOLOv8 by Ultralytics is the industry standard for real-time object detection, offering superior speed and accuracy for most detection tasks compared to cloud APIs. As an open-source model, it runs on commodity GPU hardware with no per-inference fees.
AWS Rekognition vs Self-Hosted YOLOv8 Pricing
AWS Rekognition DetectLabels charges $1.00 per 1,000 images (first 1M/month), dropping to $0.80/1K for 1-10M and $0.60/1K for 10M+. For video analysis, Rekognition charges $0.10 per minute. Self-hosted YOLOv8 on a single RTX 5090 processes 200-500+ frames per second for standard object detection, enabling real-time video analysis at 30fps on multiple simultaneous streams.
For a broader view of AI API vs self-hosting economics, see our cost per 1M tokens: GPU vs OpenAI analysis.
Cost Comparison by Image Volume
| Monthly Images | AWS Rekognition | Self-Hosted YOLOv8 (1x RTX 5090) | Savings |
|---|---|---|---|
| 10,000 | $10.00 | ~$199/mo (fixed) | API cheaper |
| 100,000 | $100 | ~$199/mo (fixed) | API cheaper |
| 200,000 | $200 | ~$199/mo (fixed) | ~Break-even |
| 1,000,000 | $1,000 | ~$199/mo (fixed) | 80% cheaper |
| 5,000,000 | $4,200 | ~$199/mo (fixed) | 95% cheaper |
| 10,000,000 | $7,400 | ~$199/mo (fixed) | 97% cheaper |
| 100,000,000 | $61,400 | ~$599/mo (3 GPUs) | 99% cheaper |
For video surveillance or continuous monitoring, the numbers are even more stark. A single security camera at 30fps generates 2.6M frames per day (78M per month). At AWS pricing, that is $62,000+ per camera per month. Self-hosted YOLOv8 handles multiple cameras on one GPU.
Break-Even Analysis
At $1.00 per 1,000 images, break-even occurs at 199,000 images per month. For video workloads, a single 30fps camera stream generates 78M frames per month — making the API cost prohibitive for any real-time application. Self-hosting is the only viable option for continuous video analysis.
See our GPU vs API break-even guide for the methodology, and compare with our PaddleOCR vs Google Vision comparison for another computer vision cost matchup.
Savings at Scale
| Monthly Images | AWS Rekognition Cost | Self-Hosted Cost | Monthly Savings | Annual Savings |
|---|---|---|---|---|
| 1,000,000 | $1,000 | $199 | $801 (80%) | $9,612 |
| 5,000,000 | $4,200 | $199 | $4,001 (95%) | $48,012 |
| 10,000,000 | $7,400 | $199 | $7,201 (97%) | $86,412 |
| 100,000,000 | $61,400 | $599 | $60,801 (99%) | $729,612 |
At 100M images per month (a modest multi-camera deployment), self-hosting saves over $729,000 annually. This is why virtually no production video analytics system uses cloud APIs for inference.
Speed and Throughput Differences
YOLOv8 on an RTX 5090 processes 200-500 images per second for detection tasks, with sub-5ms latency per frame. AWS Rekognition has network round-trip latency of 100-500ms per image, making it unsuitable for real-time applications. For batch processing, YOLOv8 with batch inference scales to 1,000+ images per second on high-end GPUs.
YOLOv8 also supports custom training — you can fine-tune it on your specific objects, defect types, or scene categories. This is not possible with Rekognition. Deploy on GigaGPU dedicated servers and see our cheapest GPU for inference guide for hardware recommendations.
When to Self-Host Object Detection
For occasional image labelling under 200K images per month, AWS Rekognition works. For any real-time, video-based, or high-volume object detection workload, self-hosted YOLOv8 on GigaGPU dedicated GPU hardware is the only sensible option. Lower latency, higher throughput, full customisation, and 80-99% cost savings.
Compare your options with our GPU vs API cost comparison tool, or learn about the API cost trap that makes cloud AI untenable at scale.
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