Cloudflare Workers vs AWS Lambda: Real Cost Comparison 2026
Why edge compute is quietly killing traditional serverless — with actual numbers
The serverless landscape has fundamentally shifted in 2026. Cloudflare Workers' edge-first architecture and simplified pricing model are challenging AWS Lambda's dominance. But which one actually costs less for your workload?
We analyzed real-world scenarios from 10,000 to 10 million requests per month. The results might surprise you.
TL;DR: Which One Should You Choose?
Choose Cloudflare Workers If:
- ✅ You have low CPU, high I/O workloads (APIs, webhooks)
- ✅ You need global edge deployment (sub-50ms latency)
- ✅ You want predictable pricing (no cold start costs)
- ✅ Your traffic is bursty or unpredictable
- ✅ You're building with JavaScript/TypeScript
Best for: APIs, webhooks, edge functions, real-time apps
Choose AWS Lambda If:
- ✅ You have CPU-intensive workloads (image processing, ML)
- ✅ You need multi-language support (Python, Go, Java, etc.)
- ✅ You require long execution times (up to 15 minutes)
- ✅ You need more memory (up to 10GB)
- ✅ You're already deep in AWS ecosystem
Best for: Data processing, batch jobs, ML inference, complex workflows
Pricing Breakdown: 2026 Edition
Cloudflare Workers Pricing
Cloudflare's pricing is beautifully simple — you only pay for CPU time, never for I/O wait time:
| Component | Free Tier | Paid Tier ($5/month) |
|---|---|---|
| Requests | 100,000/day | 10M included, then $0.30/1M |
| CPU Time | 10ms per invocation | 30M ms included, then $0.02/1M ms |
| Duration Limit | 30 seconds | 30 seconds |
| Memory | 128 MB | 128 MB |
🔥 Key Advantage: Workers only charge for CPU time. If your function spends 200ms waiting for a database response but only uses 15ms of CPU, you're only charged for 15ms.
AWS Lambda Pricing
Lambda's pricing is more complex, charging for both requests and duration (including I/O wait time):
| Component | Free Tier | Paid Tier |
|---|---|---|
| Requests | 1M/month | $0.20 per 1M |
| Duration (x86) | 400,000 GB-seconds | $0.0000166667 per GB-second |
| Duration (ARM) | 400,000 GB-seconds | $0.0000133333 per GB-second (20% cheaper) |
| Duration Limit | 15 minutes | 15 minutes |
| Memory | 128 MB - 10 GB | 128 MB - 10 GB |
⚠️ Hidden Cost: Lambda charges for total duration, including time spent waiting on I/O. A 200ms function that only uses 15ms of CPU still costs you for the full 200ms.
Real-World Cost Scenarios
Scenario 1: API Gateway (Low CPU, High I/O)
Use Case: REST API that fetches data from a database and returns JSON
- 100,000 requests/month
- Average duration: 220ms
- Average CPU time: 15ms
- Memory: 128 MB
| Provider | Requests | Compute | Subscription | Total/Month |
|---|---|---|---|---|
| Cloudflare Workers | $0.00 | $0.00 | $5.00 | $5.00 |
| AWS Lambda (x86) | $0.00 | $0.37 | $0.00 | $0.37 |
💡 Winner: AWS Lambda — At this scale, Lambda's free tier covers everything. Workers requires the $5 subscription.
Scenario 2: Webhook Handler (1M requests/month)
Use Case: Processing incoming webhooks from Stripe, GitHub, etc.
- 1,000,000 requests/month
- Average duration: 180ms
- Average CPU time: 12ms
- Memory: 128 MB
| Provider | Requests | Compute | Subscription | Total/Month |
|---|---|---|---|---|
| Cloudflare Workers | $0.00 | $0.00 | $5.00 | $5.00 |
| AWS Lambda (x86) | $0.00 | $3.00 | $0.00 | $3.00 |
💡 Winner: AWS Lambda — Still cheaper due to generous free tier.
Scenario 3: High-Traffic API (10M requests/month)
Use Case: Mobile app backend serving millions of users
- 10,000,000 requests/month
- Average duration: 200ms
- Average CPU time: 15ms
- Memory: 128 MB
| Provider | Requests | Compute | Subscription | Total/Month |
|---|---|---|---|---|
| Cloudflare Workers | $0.00 | $3.00 | $5.00 | $8.00 |
| AWS Lambda (x86) | $1.80 | $26.67 | $0.00 | $28.47 |
🔥 Winner: Cloudflare Workers — 72% cheaper! The CPU-only billing model shines at scale.
Scenario 4: Image Processing (CPU-Intensive)
Use Case: Resizing and optimizing uploaded images
- 500,000 requests/month
- Average duration: 3 seconds
- Average CPU time: 2.8 seconds
- Memory: 512 MB
| Provider | Requests | Compute | Subscription | Total/Month |
|---|---|---|---|---|
| Cloudflare Workers | $0.00 | $28.00 | $5.00 | $33.00 |
| AWS Lambda (x86) | $0.00 | $20.83 | $0.00 | $20.83 |
💡 Winner: AWS Lambda — For CPU-heavy workloads, Lambda's ability to allocate more memory and optimize for compute wins.
Performance: Edge vs Regional
Cloudflare Workers: Global Edge Network
- 330+ locations worldwide — Your code runs within 50ms of 95% of the world's population
- Zero cold starts — Workers are always warm, no initialization delay
- Instant global deployment — Deploy once, run everywhere in seconds
- Automatic failover — If one edge location fails, traffic routes to the next closest
AWS Lambda: Regional Deployment
- 33 regions — You choose specific regions to deploy to
- Cold starts — 100-500ms delay for first invocation (Java can be 1-2 seconds)
- SnapStart for Java — Reduces cold starts by 90% (Java only, as of 2026)
- Multi-region requires setup — Need to manually deploy to multiple regions
Real-World Impact: A user in Sydney accessing a US-based Lambda function might see 200-300ms latency. With Workers, that same user gets sub-50ms response from the Sydney edge location.
Developer Experience
Cloudflare Workers
- Languages: JavaScript, TypeScript, Rust, C, C++
- Runtime: V8 isolates (faster than containers)
- Local Dev: Wrangler CLI with hot reload
- Deployment:
wrangler deploy(2-3 seconds globally) - Debugging: Tail logs, Logpush to external services
- Storage: KV (key-value), R2 (S3-compatible), D1 (SQLite), Durable Objects
AWS Lambda
- Languages: Node.js, Python, Java, Go, Ruby, .NET, custom runtimes
- Runtime: Firecracker microVMs
- Local Dev: SAM CLI, LocalStack, or Docker
- Deployment: SAM, CDK, Serverless Framework, or Console
- Debugging: CloudWatch Logs, X-Ray tracing, Lambda Insights
- Storage: S3, DynamoDB, RDS, EFS, and 200+ AWS services
Limitations to Know
Cloudflare Workers Limitations
- ❌ Fixed 128 MB memory — Can't increase for memory-intensive tasks
- ❌ 30-second timeout — Not suitable for long-running jobs
- ❌ No native Node.js — Some npm packages won't work
- ❌ Limited CPU time — 50ms on free tier, 30 seconds on paid
- ❌ No file system access — Must use KV, R2, or external storage
AWS Lambda Limitations
- ❌ Cold starts — 100-500ms delay (can be 1-2s for Java)
- ❌ Regional deployment — Not automatically global
- ❌ Complex pricing — Harder to predict costs
- ❌ VPC cold starts — Even slower if using VPC (though improved in 2024)
- ❌ Package size limits — 50 MB zipped, 250 MB unzipped
Migration Tips
Moving from Lambda to Workers
// Lambda Handler
exports.handler = async (event) => {
const body = JSON.parse(event.body);
return {
statusCode: 200,
body: JSON.stringify({ message: "Hello" })
};
};
// Workers Equivalent
export default {
async fetch(request) {
const body = await request.json();
return new Response(
JSON.stringify({ message: "Hello" }),
{ headers: { "Content-Type": "application/json" } }
);
}
}; Moving from Workers to Lambda
// Workers Handler
export default {
async fetch(request) {
return new Response("Hello World");
}
};
// Lambda Equivalent
exports.handler = async (event) => {
return {
statusCode: 200,
body: "Hello World"
};
}; Final Verdict: Which Should You Choose?
Choose Cloudflare Workers When:
- ✅ You're building APIs, webhooks, or edge functions
- ✅ You need global low latency (sub-50ms)
- ✅ Your workload is I/O-heavy (database calls, API requests)
- ✅ You want predictable costs at scale
- ✅ You're comfortable with JavaScript/TypeScript
- ✅ You value zero cold starts
Typical Cost: $5-50/month for most apps
Choose AWS Lambda When:
- ✅ You need CPU-intensive processing (image/video, ML)
- ✅ You require multi-language support
- ✅ You need long execution times (up to 15 minutes)
- ✅ You need more than 128 MB memory
- ✅ You're already invested in AWS
- ✅ You need VPC access to private resources
Typical Cost: $0-100/month depending on usage
The Bottom Line
For most modern web applications (APIs, webhooks, edge functions), Cloudflare Workers are 50-80% cheaper at scale and offer better global performance.
For compute-heavy workloads (image processing, ML inference, data transformation), AWS Lambda is still the better choice due to flexible memory allocation and longer execution times.