Cloudflare verdict: the bandwidth and edge story is unbeatable; DX still catching up

How we tested

The verdict, in 60 seconds

Where the 93 comes from

What it gets right

Bandwidth pricing changed the math for the entire category

Pages bandwidth is unlimited and free. Workers requests cost $0.30/M after the included 10M. R2 charges nothing for egress. Compare to S3 + CloudFront where 1TB of egress costs $90 ($0.09/GB), or Vercel's $0.15/GB.

Realistic example from our test: a media site serving 5TB/month would cost $450 on AWS (egress) or $750 on Vercel (bandwidth tier). On Cloudflare: $0 for Pages bandwidth + ~$60 for R2 storage. This is not a minor optimization — it's a structural cost advantage.

V8 isolates beat container serverless on latency

Workers cold starts measured 5-15ms in our testing. Compare AWS Lambda cold start: 200-800ms (warm: 50-150ms). Vercel Fluid Compute: 28ms (warm: 8ms). Cloudflare wins both metrics by physics — V8 isolates initialize in single-digit milliseconds because the JavaScript engine is already running, just executing different code.

For latency-sensitive workloads (auth, personalization, AI streaming first-token), the difference is user-visible.

330+ PoPs is a moat

Vercel has 100+. AWS CloudFront has 600+ but most are 'cache only' with no compute. Cloudflare Workers run on all 330+ PoPs as full compute nodes. For global SaaS this means your users in Mumbai, Lagos, São Paulo get sub-50ms TTFB without you doing anything.

We measured: a single Workers deployment served all 195 countries with p95 TTFB under 80ms. No region configuration, no CDN setup.

R2 + zero egress unlocks new architectures

Storage is $0.015/GB-month (same as S3). Egress is free. Operations are cheaper than S3. The net is that workloads previously priced out of cloud (large video catalogs, AI model serving with frequent downloads, ML dataset hosting) become economically viable.

Our test workload: 8TB media catalog with 40TB/month egress. AWS S3 + CloudFront: $3,820/month. R2: $120/month. The math is real.

Where it falls short

DX still trails Vercel

Wrangler CLI works but doesn't feel as polished as the Vercel CLI. The dashboard takes more clicks to surface what you want. Git integration is functional but not as tight as Vercel's PR previews (Pages does generate them but they're slower to spin up).

For solo devs and small teams used to Vercel's hand-holding, the first week on Cloudflare feels like driving a manual after years of automatic.

128MB Workers memory is a real constraint

Workers cap at 128MB memory and ~30 seconds CPU time. For most edge workloads (auth, personalization, API gateways) this is fine. For anything with significant in-memory state (large data transforms, ML preprocessing, video manipulation) you'll hit walls and need to architect around them.

Container Workers (beta in 2025) lift this ceiling but you lose some of the V8 isolate latency advantage.

D1 maturity still has rough edges

D1 is SQLite at the edge with strong consistency reads and eventually-consistent writes. Read-heavy workloads work great. Write contention is the failure mode — schema migrations on production databases sometimes fail in ways that require manual intervention. We hit one such case during testing.

For mission-critical transactional workloads, pair with a real Postgres until D1 hits v2.0 maturity.

Support is the platform's worst dimension

Free tier: community Discord, GitHub issues, Stack Overflow. Pro Workers ($5/mo): email support but median response was 36 hours in our testing. Business plan: same email tier. Enterprise: dedicated CSM.

For production workloads where outages cost real money, the support story pushes you toward Enterprise — at which point Vercel's Pro support starts to look more competitive on total cost.

Documentation gaps for advanced patterns

Workers basics are well-documented. Durable Objects (stateful Workers), Hyperdrive (database connection pooling at the edge), Queues, Pub/Sub — these advanced features have documentation that assumes you've already read deeply elsewhere. Community blog posts fill some gaps; official docs catch up slowly.

Pricing reality

Benchmark matrix

Cost-to-performance ratio

Hardware & software stack

Scenario simulation: what Cloudflare costs for your work

Use-case match matrix

Stability & uptime history

Longitudinal pricing data

Community sentiment

Who should avoid this

Skip this if you fall into any of these buckets. Naming it up-front beats a support ticket later.

• Teams deeply invested in Next.js-specific Vercel features they can't refactor
• Workloads requiring more than 128MB working memory per request
• Operations needing white-glove support on standard plans
• Mission-critical write-heavy databases (use real Postgres, not D1)
• Workflows that depend on AWS-native services (SQS, DynamoDB, etc.) tightly
• Teams without an engineer comfortable with edge-first thinking

Testing evidence

region              cold_p50    cold_p95    cold_p99
us-east             6ms         10ms        14ms
us-west             5ms         9ms         12ms
eu-west             6ms         11ms        15ms
ap-southeast        8ms         13ms        18ms
ap-northeast        7ms         12ms        16ms
sa-east             9ms         14ms        21ms

component               AWS S3+CloudFront    Cloudflare R2+Pages
storage (8TB)           $184                 $120
egress (40TB)           $3,600               $0
requests (50M)          $36                  $15
TOTAL / month           $3,820               $135
ANNUAL SAVINGS:                              $44,220

ROI calculator

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The verdict

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