The Cost of Inference: AWS SageMaker vs. EC2

You’ve trained your model. Now comes the real challenge: deploying it for predictions. But which path will cost you less? This article pits Amazon SageMaker against Amazon EC2, revealing the hidden costs and unexpected savings in the race to inference.

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Introduction to SageMaker Inference Endpoints and EC2

Before we jump into the cost comparison, let’s briefly understand what these two services offer.

Amazon SageMaker Inference Endpoints
SageMaker is a fully managed service that provides tools for building, training, and deploying machine learning models. SageMaker Inference Endpoints are designed specifically for deploying models at scale. They handle the infrastructure, scaling, and maintenance, allowing data scientists to focus on the models rather than the underlying infrastructure. SageMaker also provides built-in features like auto-scaling, monitoring, and A/B testing.

Amazon EC2
Amazon EC2 (Elastic Compute Cloud) is a foundational AWS service that provides resizable compute capacity in the cloud. With EC2, you have full control over the instance type, operating system, and software stack. While this flexibility is powerful, it also means you’re responsible for managing the infrastructure, including scaling, monitoring, and maintenance.

For this comparison, we’ll focus on deploying a machine learning model for inference on both platforms, using the same instance type: g4dn.xlarge. This instance type is optimized for machine learning inference workloads, as it includes NVIDIA T4 GPUs.

The Cost Comparison: SageMaker Inference Endpoint vs. EC2

To compare the costs, I used the AWS Pricing Calculator and created a detailed estimate for both deployment options. The results are clear: deploying the same machine learning model on an EC2 instance is significantly cheaper than using a SageMaker Inference Endpoint.

To determine how much more costly SageMaker is compared to EC2, we can calculate the percentage difference between the two costs. Here’s the breakdown:

• SageMaker Cost: $529.92
• EC2 Cost: $383.98

Step 1: Calculate the Difference in Cost

First, find the absolute difference between the two costs:

Difference=SageMaker Cost-EC2 Cost=529.92-383.98=145.94

Step 2: Calculate the Percentage Increase

Next, calculate the percentage increase of SageMaker’s cost over EC2’s cost:

Here is the link of my estimate exported from AWS pricing .

When Does SageMaker Make Sense?

SageMaker Inference Endpoints have their place. Here are a few scenarios where SageMaker might be worth the extra cost:

1. Managed Infrastructure: If your team lacks the expertise or resources to manage EC2 instances, SageMaker’s fully managed service can save time and effort.
2. Auto-scaling: SageMaker’s built-in auto-scaling is ideal for applications with variable traffic patterns.
3. Advanced Features: If you need features like A/B testing, model monitoring, or multi-model endpoints, SageMaker provides these out of the box.

However, if cost is your primary concern and you’re comfortable managing your own infrastructure, EC2 is the should be your choice.

Disclaimer

The cost comparison provided in this blog post focuses solely on the compute costs (instance and endpoint fees) for deploying a machine learning model on Amazon SageMaker Inference Endpoints versus Amazon EC2. Storage costs (e.g., model artifacts, data storage) and network costs (e.g., data transfer in/out) have been intentionally excluded to simplify the comparison. These additional costs can vary significantly depending on your specific use case, such as the size of your model, the volume of data processed, and the region in which you operate. Always consider these factors when making a final decision, and use the AWS Pricing Calculator for a comprehensive estimate tailored to your workload.

Conclusion

In this cost comparison, we’ve seen that deploying a machine learning model on an EC2 instance is significantly cheaper than using a SageMaker Inference Endpoint. For the same g4dn.xlarge instance, EC2 costs approximately 38.0% less per month. While SageMaker offers valuable features like managed infrastructure and auto-scaling, these come at a premium.

Ultimately, the choice between SageMaker and EC2 depends on your specific needs and constraints. If cost is a top priority and you have the expertise to manage your own infrastructure, EC2 is the way to go. On the other hand, if you value convenience and advanced features, SageMaker might be worth the investment.

Note: The cost estimates in this blog post are based on the AWS Pricing Calculator as of Jan 2025. Actual costs may vary depending on usage patterns, region, and other factors. Always refer to the latest AWS pricing documentation for the most accurate information.

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