Compute vs EC2 Savings Plan: Complete Decision Guide (2026)

You've done the math and know Savings Plans will save you money. But now you face a choice that could mean thousands of dollars difference: Compute Savings Plan or EC2 Instance Savings Plan?

Both promise significant discounts. Both require a commitment you can't escape. Choose wrong, and you either leave money on the table with a lower discount or lock yourself into infrastructure that no longer fits your needs.

Here's the reality: The difference between 66% and 72% savings sounds small until you run the numbers on a $50,000/month compute spend. That 6% becomes $3,000/month or $108,000 over three years. But flexibility has its own value when your architecture evolves.

By the end of this guide, you'll know exactly which plan fits your workload, see the real dollar difference across common scenarios, and have a clear purchase strategy. Let's start with the quick answer, then dig into the details.

TL;DR - Which Savings Plan Should You Choose?

If you need a quick answer before diving into details, here's the decision framework that works for most organizations.

The core tradeoff is straightforward: Compute Savings Plans offer flexibility at up to 66% discount, while EC2 Instance Savings Plans offer maximum savings at up to 72% but lock you to a specific instance family and region.

The 30-Second Decision Rule

Choose Compute Savings Plan if any of these apply:

• You use Lambda or Fargate (at all)
• You deploy across multiple AWS regions
• You might change instance families in the next 1-3 years
• Your architecture is evolving or you're modernizing to containers/serverless
• You run workloads across EC2, Fargate, AND Lambda together

Choose EC2 Instance Savings Plan if ALL of these apply:

• You run EC2 only (no Lambda, no Fargate)
• You're committed to a specific instance family (M5, C5, R5, etc.)
• You operate primarily in one region
• Your architecture is stable for the 1-3 year term
• Maximum discount is your priority

My recommendation for most organizations: Start with Compute Savings Plans for the flexibility. Add EC2 Instance Savings Plans later for your stable baseline once you've proven your usage patterns are predictable.

Now let's understand what you're actually comparing.

What Are Compute and EC2 Instance Savings Plans?

Before choosing between these two options, you need to understand what they share and where they differ. Both are commitment-based pricing models from AWS, but they make different tradeoffs between flexibility and discount depth.

The core concept is identical: you commit to a dollar-per-hour spend ($/hour) for 1 or 3 years. AWS applies discounted rates to your usage up to that commitment. Any usage beyond your commitment gets charged at On-Demand rates.

What you're really choosing is how much flexibility you want in exchange for your commitment.

Compute Savings Plans Explained

Compute Savings Plans provide maximum flexibility. Your commitment applies automatically across:

• EC2 instances: Any instance family, size, region, OS, AZ, or tenancy
• AWS Fargate: vCPU and memory costs (OS license fees excluded)
• AWS Lambda: All compute duration charges
• Container services: EC2 instances in EKS, ECS, and EMR clusters

The discount ceiling is up to 66% off On-Demand rates. You sacrifice about 6% potential savings compared to EC2 Instance Savings Plans, but you gain the freedom to change your infrastructure without losing your discount.

Coverage limitation to know: Virtual u-type instances are covered, but U-type metal instances are not supported under any Savings Plan.

EC2 Instance Savings Plans Explained

EC2 Instance Savings Plans offer the lowest prices in exchange for more specificity. You commit to:

• A specific instance family: For example, M5, C5, or R5
• A specific AWS Region: For example, us-east-1

Within those constraints, you retain flexibility on instance size, OS, AZ, and tenancy. You can switch from c5.large to c5.4xlarge without issue. You can change from Linux to Windows. But you cannot switch from C5 to M5, and you cannot use your commitment in a different region.

The discount ceiling is up to 72% off On-Demand rates. That extra 6% over Compute Savings Plans can be significant at scale, but you're betting on your architecture staying stable.

What's not covered: Lambda and Fargate are not covered by EC2 Instance Savings Plans. If you use either, you need Compute Savings Plans to get any discount on that usage.

How Both Differ from Reserved Instances

You might be wondering where Reserved Instances fit into this picture. The key difference is the commitment type:

AWS now recommends Savings Plans for most workloads due to their flexibility. Reserved Instances still have a use case when you need guaranteed capacity in a specific AZ, but for pure cost optimization, Savings Plans are the modern approach.

For a comprehensive overview of all four Savings Plans types, including Database Savings Plans for RDS/Aurora/DynamoDB and SageMaker, see the AWS Savings Plans guide.

Head-to-Head Comparison: Key Differences

Now that you understand the basics, let's compare these two options across the dimensions that matter for your decision. The differences become much clearer when you see them side by side.

Flexibility vs Maximum Discount

This is the fundamental tradeoff. Here's what you're choosing between:

Compute Savings Plans (up to 66% discount):

• Change instance families freely (M5 to C6i to R6g)
• Move workloads between regions
• Shift from EC2 to Fargate to Lambda
• Adapt to new instance generations as AWS releases them

EC2 Instance Savings Plans (up to 72% discount):

• Locked to one instance family (e.g., M5)
• Locked to one region (e.g., us-east-1)
• No coverage for Fargate or Lambda
• Higher discount compensates for reduced flexibility

The 6% difference sounds small, but let's put it in perspective: on a $10/hour commitment over 3 years, that's roughly $15,000 in additional savings if you go with EC2 Instance Savings Plans. Whether that's worth the lock-in depends entirely on your confidence in your architecture stability.

Service Coverage Comparison

This is where the decision becomes clearer for many organizations:

The critical insight: If you use Lambda OR Fargate at all, EC2 Instance Savings Plans won't cover that usage. Compute Savings Plans are your only option for multi-service architectures.

Regional and Instance Family Constraints

The constraint differences affect your operational flexibility:

Compute Savings Plans:

• Apply globally across all AWS regions
• No instance family restrictions
• Automatically cover new instance families as AWS releases them
• Ideal for organizations with multi-region deployments or DR requirements

EC2 Instance Savings Plans:

• Locked to a single region (e.g., your commitment to M5 in us-east-1 doesn't cover M5 in us-west-2)
• Locked to a single instance family (your M5 commitment doesn't cover M6i)
• Flexible within constraints: any size (large, xlarge, 2xlarge), any OS, any AZ within the region

Complete Comparison Table

Here's the full comparison across all key dimensions:

Now that you see the differences, let's understand how these plans actually apply to your bill.

How Savings Plans Actually Apply to Your Bill

Understanding the mechanics of how discounts apply helps you avoid surprises and plan your commitment strategy effectively. The billing logic follows specific rules that matter for optimization.

Understanding the $/Hour Commitment

Both Savings Plan types work on an hourly commitment model. You commit to spending a specific dollar amount per hour (anywhere from $0.001 to $5,000). Each hour stands alone, there's no rollover of unused commitment.

Example: You have a $10/hour Compute Savings Plan commitment.

• Hour 1: Your eligible usage costs $8 at On-Demand rates. You pay $8 at the Savings Plan discounted rate. The remaining $2 of commitment is unused and lost.
• Hour 2: Your eligible usage costs $15 at On-Demand rates. You pay $10 at the Savings Plan rate. The remaining $5 is charged at On-Demand.

This "use it or lose it" model on an hourly basis is why sizing your commitment correctly matters so much. Over-committing means wasted money every hour.

Application Order: RIs, Then SPs, Then On-Demand

When you have multiple commitment types, AWS applies them in a specific order to maximize your savings:

Key detail: Within Savings Plans, AWS applies discounts based on highest savings percentage first. When multiple usages have equal savings percentages, it applies to the usage with the lowest Savings Plan rate first. This automatic optimization maximizes your savings without manual intervention.

Multi-Account Application (AWS Organizations)

If you're running multiple AWS accounts under an organization, Savings Plans benefits can be shared:

1. Owner account first: The account that purchased the Savings Plan gets its usage covered first
2. Remaining benefits shared: After the owner account's usage is covered, remaining commitment covers other accounts (if sharing is enabled)
3. Automatic optimization: AWS applies discounts to maximize overall savings across the organization

You can enable or disable discount sharing through billing preferences. For organizations with variable usage across accounts, centralized purchasing with sharing enabled typically maximizes utilization.

For guidance on structuring your AWS accounts, see the AWS Organizations guide and multi-account strategy.

The Decision Framework: When to Choose Each

Let's translate what you've learned into a practical decision framework. The right choice depends on your workload characteristics, organizational factors, and willingness to accept specific tradeoffs.

Choose Compute Savings Plan If

Compute Savings Plans are the right choice when flexibility matters more than maximizing the discount percentage:

Workload characteristics that point to Compute SP:

• Workloads span multiple instance families (you run M5, C5, AND R5)
• Multi-region deployments (production in us-east-1, DR in us-west-2)
• Mixed compute architecture using EC2 + Fargate + Lambda
• Containerized workloads on Fargate
• Serverless components using Lambda
• Plans to migrate between instance families (Intel to Graviton, for example)

Organizational factors:

• Rapidly evolving application architecture
• Cloud modernization or migration in progress
• DevOps teams actively optimizing instance types
• Uncertain future architecture requirements

The tradeoff you're accepting: 6% lower discount (66% vs 72%) in exchange for maximum flexibility. For many organizations, this insurance against architecture lock-in is worth far more than the discount difference.

Choose EC2 Instance Savings Plan If

EC2 Instance Savings Plans are the right choice when you have high confidence in your infrastructure stability:

Workload characteristics that point to EC2 Instance SP:

• Stable, predictable workloads on a specific instance family
• Single-region deployment with no planned multi-region expansion
• EC2-only architecture (no Fargate or Lambda usage)
• Mature applications with established performance requirements
• Long-running production databases that won't change instance families

Organizational factors:

• Cost optimization is the highest priority
• Workload architecture is finalized
• No planned migrations or re-architecture
• SAP, Oracle, or specialized workloads requiring specific instance families

The tradeoff you're accepting: Lock-in to a specific instance family and region for 1-3 years in exchange for the maximum 72% discount.

Visual Decision Tree

Here's the decision process visualized:

The key takeaway: if you answered "yes" to any of the first three questions, Compute Savings Plans are likely your better choice. EC2 Instance Savings Plans only make sense when ALL flexibility questions are "no."

Real-World Scenarios with Dollar Math

Abstract percentages don't tell the full story. Let's look at five common scenarios with actual cost comparisons to see how the decision plays out in practice.

Important note: Exact discount rates vary based on instance family, region, term length, and payment option. The numbers below use representative rates to illustrate the tradeoff. Use AWS Cost Explorer recommendations for your specific rates.

Scenario 1: Stable Single-Family Workload

Situation: Your company runs a production database cluster on R5 instances in us-east-1. The workload has been stable for two years and will continue unchanged.

• Baseline: 10x r5.2xlarge running 24/7 = approximately $8,000/month On-Demand
• Compute SP (66% discount): ~$2,720/month
• EC2 Instance SP (72% discount): ~$2,240/month
• Monthly difference: $480
• 3-year difference: $17,280

Recommendation: EC2 Instance Savings Plan. With a proven stable workload committed to R5 in one region, the extra $17,280 over three years is real money with minimal risk.

Scenario 2: Multi-Service Architecture (EC2 + Lambda + Fargate)

Situation: Your application uses EC2 for core services, Fargate for microservices, and Lambda for event processing. Usage splits roughly 60/25/15.

• Baseline: $10,000/month total compute spend
• EC2 Instance SP: Only covers the 60% EC2 portion (and only matching family/region)
• Compute SP: Covers all three services with single commitment

With Compute SP at 66%: All $10,000 covered = ~$3,400/month With EC2 Instance SP: $6,000 EC2 at 72% + $4,000 at On-Demand = ~$5,680/month

Monthly difference: $2,280 in favor of Compute SP 3-year difference: $82,080

Recommendation: Compute Savings Plan. This isn't even close. EC2 Instance Savings Plans can't cover Lambda or Fargate, making Compute SP the only viable option.

Scenario 3: Multi-Region Deployment

Situation: Your company operates in us-east-1 (primary) and eu-west-1 (European customers). Both regions run M5 instances. Usage is 70% us-east-1, 30% eu-west-1.

• Baseline: $15,000/month across both regions
• EC2 Instance SP for us-east-1 only: Covers 70% of usage at 72%, leaves 30% at On-Demand
• Compute SP: Covers 100% of usage across both regions at 66%

With Compute SP: $15,000 at 66% discount = ~$5,100/month With EC2 Instance SP for us-east-1: ($10,500 at 72%) + ($4,500 at On-Demand) = ~$7,440/month

Recommendation: Compute Savings Plan. Even if you bought separate EC2 Instance SPs for each region, the complexity isn't worth it for most organizations.

Scenario 4: Startup with Evolving Architecture

Situation: You're a growing startup running primarily on C5 instances today, but your team is evaluating Graviton (C6g/C7g), planning to add Lambda for async processing, and might containerize with Fargate next year.

• Current baseline: $5,000/month on C5 in us-east-1
• EC2 Instance SP (C5, us-east-1): 72% discount, but only covers C5

What happens when you migrate to Graviton? Your C5 commitment keeps charging while your C6g/C7g usage pays On-Demand. You effectively pay double until the commitment expires.

Recommendation: Compute Savings Plan. The flexibility to evolve your architecture without penalty is worth more than the 6% discount difference. For startups especially, architectural agility is a competitive advantage.

Scenario 5: Maximum Discount Priority

Situation: You're a mature enterprise with a 5-year-old application running on M5 instances. The application is stable, cost optimization is a board-level priority, and there's zero appetite for infrastructure changes.

• Baseline: $50,000/month on M5 in us-east-1
• Compute SP (66%): ~$17,000/month
• EC2 Instance SP (72%): ~$14,000/month
• Monthly difference: $3,000
• 3-year difference: $108,000

Recommendation: EC2 Instance Savings Plan. With a truly stable workload and cost optimization as the priority, the $108,000 savings over three years justifies the lock-in.

Scenario Summary

For help modeling costs with your specific instance types and usage patterns, the EC2 pricing calculator can help you estimate the On-Demand baseline.

Multi-Service Strategy: EC2 + Lambda + Fargate

The question I see most often about Savings Plans is: "How does this work when I use EC2, Lambda, AND Fargate together?" This deserves special attention because it's where many organizations get the decision wrong.

Why Compute Savings Plans Are Required for Multi-Service

Let me be direct: if you use Lambda or Fargate at all, EC2 Instance Savings Plans will not cover that usage. This isn't a fine-print limitation; it's fundamental to how the plans work.

EC2 Instance Savings Plans are designed specifically for EC2 instances within a committed family and region. They have no mechanism to apply to Fargate or Lambda pricing structures.

Compute Savings Plans were designed to cover the full compute portfolio. A single Compute SP commitment automatically applies across:

• EC2 instances (any family, any region)
• Fargate vCPU and memory charges
• Lambda compute duration charges

How Discounts Apply Across Services

When you have a Compute Savings Plan, here's how it works across services:

For EC2: Your commitment covers On-Demand equivalent spend on any EC2 usage, regardless of instance family, size, region, or OS.

For Fargate: Your commitment covers vCPU per hour and GB per hour (memory) dimensions. Important: OS license fees (like Windows on Fargate) are NOT covered by the discount.

For Lambda: Your commitment covers compute duration charges. Request charges ($0.20 per million requests) are NOT discounted under any Savings Plan.

The system applies discounts based on what provides the highest savings percentage first. You don't need to manage allocation manually.

Calculating Commitment for Mixed Workloads

For architectures spanning multiple services, calculate your commitment based on total eligible spend:

1. Identify your baseline across all three services
2. Convert to hourly equivalent: Total monthly spend / 730 hours
3. Apply the 80% rule: Commit to 80% of your baseline hourly rate
4. Start conservative: Better to under-commit and add more later

Example calculation:

• EC2 spend: $6,000/month
• Fargate spend: $2,500/month
• Lambda compute: $1,500/month
• Total: $10,000/month = ~$13.70/hour
• Recommended commitment: ~$10-11/hour (80% of baseline)

The single Compute SP commitment covers all three services automatically. No allocation required.

The Hybrid Approach: Using Both Plan Types

A question many teams don't realize they should ask: "Can I use BOTH Compute and EC2 Instance Savings Plans together?" The answer is yes, and it's often the optimal strategy for larger organizations.

When a Combination Strategy Makes Sense

A hybrid approach works well when you have both stable and variable workloads:

Stable baseline: Production databases or core services that have run on the same instance family for years, with no plans to change.

Variable/evolving workloads: Development environments, newer applications still being optimized, or workloads that span EC2 and serverless.

By using EC2 Instance Savings Plans for the stable baseline (72% discount) and Compute Savings Plans for everything else (66% discount), you get the best of both worlds: maximum savings where you can lock in, flexibility where you need it.

Example: EC2 Instance SP for Base + Compute SP for Variable

Here's a practical implementation:

Your workload profile:

• Production R5 database cluster: $7,000/month (stable for 3+ years)
• Application servers (M5): $4,000/month (might migrate to Graviton)
• Fargate microservices: $2,000/month
• Lambda processing: $1,000/month

Hybrid strategy:

• EC2 Instance SP (R5, us-east-1): Covers $7,000/month production databases at 72% discount
• Compute SP: Covers remaining $7,000/month across M5, Fargate, and Lambda at 66% discount

Combined monthly cost: ($7,000 x 0.28) + ($7,000 x 0.34) = ~$4,340 Compute SP only: $14,000 x 0.34 = ~$4,760 Monthly savings from hybrid: ~$420

Over three years, that's roughly $15,000 in additional savings while maintaining flexibility for the variable portion of your workload.

Pitfalls to Avoid

The hybrid approach has risks if not managed carefully:

Over-complicating your portfolio: Don't create separate EC2 Instance SPs for every instance family you use. The management overhead and risk of stranded commitment rarely justifies the extra discount.

Forgetting application order: Remember that Compute SP applies before EC2 Instance SP. If your Compute SP commitment is too large, it may cover usage you intended for your EC2 Instance SP.

Double-counting baseline: Ensure you're not over-committing by counting the same usage in both plans. Size each plan independently based on what it should cover.

Commitment Sizing: How to Avoid Overcommitting

The most expensive Savings Plans mistake isn't choosing the wrong type; it's committing to too much. Once purchased, you can't modify or cancel. Every hour of unused commitment is money lost.

Analyzing Historical Usage Patterns

Start with data, not guesses:

1. Use Cost Explorer: Look at your On-Demand compute spend over the last 30-60 days
2. Identify baseline vs peaks: Your baseline is the consistent floor, not average including spikes
3. Filter by service: Understand the split between EC2, Fargate, and Lambda
4. Check for anomalies: Exclude one-time events (load tests, migrations) from your analysis

AWS Cost Explorer's Savings Plans recommendations use similar logic, but they optimize for maximum savings, not risk management. Use them as input, not as your final decision.

The 80% Rule: Start Conservative

Here's the principle that prevents costly mistakes: commit to 80% of your baseline usage, not 100%.

Why 80%?

• Leaves room for normal variation
• Accounts for potential workload reduction
• Allows flexibility for optimization efforts that reduce compute needs
• Better to under-commit and pay some On-Demand than over-commit and waste money

Example:

• Your analysis shows $10/hour baseline compute spend
• AWS recommends $10/hour commitment
• My recommendation: Start with $8/hour commitment
• After 30-60 days at high utilization, add another $1-2/hour

Phased Commitment Approach

For larger commitments, spread your purchases over time:

Phase 1 (Month 1): Purchase 60-70% of your estimated optimal commitment

Phase 2 (Month 2-3): Monitor utilization. If consistently above 95%, purchase additional 15-20%

Phase 3 (Ongoing): Quarterly reviews to assess need for additional coverage

This approach has two benefits:

1. Reduces risk of over-committing based on temporary usage patterns
2. Spreads expiration dates so you're not renewing everything at once

For your first Savings Plans purchase, I recommend 1-year terms over 3-year. The discount difference isn't dramatic, and you maintain flexibility to adjust your strategy as you learn.

Getting Started: Purchase and Setup

Ready to purchase? Here's how to use AWS's tools effectively and avoid common setup mistakes.

Using AWS Cost Explorer Recommendations

AWS generates personalized recommendations based on your historical usage. Find them at: AWS Console > Billing and Cost Management > Savings Plans > Recommendations

Customization options:

• Savings Plan type: Compute or EC2 Instance (choose based on your analysis)
• Term: 1 year or 3 years
• Payment option: All Upfront, Partial Upfront, No Upfront
• Lookback period: 7, 30, or 60 days

Key metrics provided:

• Recommended hourly commitment ($/hour)
• Estimated monthly savings
• Expected utilization percentage
• Estimated ROI

Critical limitation: Recommendations are based on historical usage only. They don't account for planned changes, migrations, or workload growth. Always validate recommendations against your known future plans.

Payer vs Linked Account: Where to Purchase

If you're using AWS Organizations, you have a choice:

Payer (Management) Account View:

• Analyzes organization-wide usage across all accounts
• Higher recommended commitments
• Maximizes savings at the organization level
• Benefits can be shared across accounts (if enabled)

Linked (Member) Account View:

• Focuses on that specific account's usage
• More conservative recommendations
• Benefits stay with the purchasing account

My recommendation: For most organizations, purchase from the management account with organization-wide sharing enabled. This maximizes utilization and simplifies management.

1-Year vs 3-Year: Which Term Length?

For first-time buyers: Start with 1-year terms. The discount difference (typically 5-10% additional savings for 3-year) isn't worth the risk until you've proven your usage patterns are stable.

Payment Options: All Upfront, Partial, or No Upfront

For risk management: No Upfront provides the lowest financial risk. If your workload changes dramatically, you've only committed to hourly payments rather than having capital locked in upfront.

After Purchase: Monitoring and Optimization

Purchasing is step one. Ongoing monitoring ensures you're getting expected value and helps you plan renewals intelligently.

Key Metrics: Utilization and Coverage

Two metrics matter for Savings Plans health:

Utilization: Are you using what you committed to?

• Formula: (SP commitment used) / (Total SP commitment) x 100%
• Goal: 100% (using everything you pay for)
• Low utilization problem: You over-committed and are wasting money each hour

Coverage: What percentage of eligible usage is discounted?

• Formula: (Usage covered by SP) / (Total eligible usage) x 100%
• Goal: 70-90% (leave room for peaks at On-Demand rates)
• Low coverage opportunity: Room for additional Savings Plans purchases

Example interpretation:

• 95% utilization, 70% coverage = Good. You're using your commitment efficiently and have room for growth.
• 60% utilization, 95% coverage = Problem. You over-committed; 40% of your commitment is wasted each hour.

Setting Up Budget Alerts

Configure alerts to catch problems early:

Utilization alert: Set threshold at 80%. If utilization drops below 80%, you're wasting 20%+ of your commitment. Investigate why and adjust future purchases.

Coverage alert: Set threshold based on your target (e.g., 70%). If coverage drops significantly, you may have opportunity for additional purchases.

Expiration alert: Set reminders 30-60 days before Savings Plans expire. This gives you time to analyze and queue renewal purchases.

AWS Budgets supports Savings Plans-specific budgets with email, SNS, and Chatbot (Slack/Chime) notifications.

Quarterly Review Process

Establish a regular cadence:

Monthly quick check (5 minutes):

• Is utilization above 95%?
• Any expiring Savings Plans in next 90 days?

Quarterly deep review (30-60 minutes):

• Analyze utilization trends over the quarter
• Evaluate coverage and identify purchase opportunities
• Review upcoming expirations and plan renewals
• Assess architecture changes that might affect future purchases

For teams using Infrastructure as Code, consider adding budget monitoring through AWS CDK. See CDK best practices for implementation patterns.

Conclusion and Next Steps

Choosing between Compute and EC2 Instance Savings Plans comes down to one question: Is the extra 6% discount worth locking into a specific instance family and region?

Key takeaways to remember:

1. Compute Savings Plans (up to 66%) offer flexibility across any instance family, any region, plus Lambda and Fargate coverage. Choose this if your architecture might evolve or you use multiple compute services.

2. EC2 Instance Savings Plans (up to 72%) offer maximum discount for stable, single-family, single-region EC2 workloads. Choose this only when you're confident your infrastructure won't change.

3. Most organizations should start with Compute Savings Plans for flexibility, then add EC2 Instance Savings Plans for proven stable baselines once usage patterns are established.

4. Start conservative: Commit to 80% of your baseline usage initially. You can always add more.

5. Monitor utilization monthly: Low utilization means over-commitment. Target 95%+ utilization.

Your next step: Open AWS Cost Explorer, look at your last 30 days of compute spend across EC2, Lambda, and Fargate. Run the Savings Plans recommendations for both Compute and EC2 Instance types. See which fits your usage pattern better.

For a comprehensive overview of all four Savings Plans types including Database Savings Plans for database workloads, see the complete AWS Savings Plans guide.

What's your biggest question about choosing between these Savings Plans types? Drop a comment below and I'll help you work through it.

FAQ: Your Savings Plans Questions Answered