AWS vs Azure vs GCP: Comparing Cloud Costs in 2026

If you’re managing cloud infrastructure in 2026, you already know the headache: aws vs azure vs gcp cost comparison is a moving target. The three major hyperscalers—Amazon Web Services, Microsoft Azure, and Google Cloud Platform—all compete fiercely on price, yet each structures its billing in ways that make apples-to-apples comparisons genuinely difficult. Compute, storage, and data transfer each carry their own pricing logic, and the provider that looks cheapest for one workload can end up the most expensive for another.

This guide breaks down the real cost dimensions—compute, storage, data transfer, and the hidden fees that silently inflate your bill—so you can make an informed decision based on your workloads, not marketing claims. Whether you’re selecting your first cloud provider, managing a multi-cloud estate, or re-evaluating an existing commitment, this aws vs azure vs gcp cost comparison gives you the numbers and the context to act on them.

Compute Pricing Comparison

Compute is typically the largest line item on any cloud bill, so it’s where the aws vs azure vs gcp cost comparison hits hardest. All three providers offer three main pricing models: on-demand (pay-as-you-go), reserved or committed-use discounts (1–3 year commitments), and spot or preemptible instances (discounted capacity that can be reclaimed with short notice).

For a general-purpose virtual machine with 2 vCPUs and 4 GB of RAM in a US East region (as of late 2025 pricing), here’s how the three providers stack up:

Pricing Model	AWS (t3.medium)	Azure (B2s)	GCP (e2-medium)
On-Demand	~$30/month	~$30/month	~$24/month
Reserved (1-year, upfront)	~$18/month	~$17/month	~$15/month
Spot / Preemptible	~$9/month	~$3/month	~$6/month

On paper, GCP looks cheapest for on-demand and reserved pricing thanks to its automatic sustained-use discounts (up to 30% off after 25% monthly utilization—no manual configuration required). Azure, meanwhile, offers aggressively priced spot instances and the largest x86-to-Arm price gap of the three (roughly 65% on on-demand and 69% on spot), making Arm-based workloads particularly attractive on Azure. AWS Reserved Instances and Savings Plans can cut on-demand rates by up to 72%, and Azure’s Reservations and Savings Plans reach similar discounts, but you have to commit and configure them manually—unlike GCP’s automatic discounts.

The takeaway: for steady, predictable workloads, all three are close enough that committed-use discounts erase most of the difference. For bursty or interruptible workloads, Azure spot and GCP preemptible instances offer the biggest savings. The real cost divergence shows up elsewhere.

Storage Costs

Object storage is functionally similar across AWS S3, Azure Blob Storage, and Google Cloud Storage, but the per-GB pricing and associated operation fees differ in ways that matter at scale. In comparable US East regions, standard object storage ranges from roughly $0.023/GB-month on the high end to $0.015/GB-month on the low end, with Azure generally offering the most cost-effective standard-tier pricing and GCP recently raising prices across several core storage services.

But list price is only part of the story. Each provider charges separately for storage operations—PUT, GET, LIST, and DELETE requests—and these per-request fees can dominate your storage bill for write-heavy or frequently-accessed workloads. Archive and cold-storage tiers (S3 Glacier, Azure Archive Storage, GCP Archive) offer dramatically lower per-GB rates but impose retrieval fees and minimum-duration charges that can negate savings if you access data more often than expected.

Block storage for virtual machines tells a similar story: expect $0.08–$0.23 per GB-month depending on performance tier and provider. Higher-performance SSD tiers cost more but are often necessary for database workloads. The key is matching the tier to actual IOPS requirements—over-provisioning storage performance is one of the most common sources of cloud waste.

Data Transfer Costs

Data transfer—specifically egress—is where cloud costs quietly explode. All three providers give you the first 100 GB/month of internet egress for free, but after that, the charges mount quickly:

• AWS: ~$0.09/GB for internet egress after the free tier.
• Azure: ~$0.087/GB for the first 5 TB—the cheapest standard egress of the three.
• GCP: ~$0.12/GB for the first terabyte, making it the most expensive standard egress rate.

Cross-region and cross-availability-zone transfers add another layer. Moving data between AWS regions can cost $0.01–$0.02/GB, and even transfers between availability zones within the same region incur charges—costs that are easy to overlook until they appear on your invoice. Azure and GCP apply similar inter-region and inter-zone fees, though the exact rates differ by route.

For data-intensive applications—media streaming, analytics, or multi-region APIs—egress can easily exceed compute costs. If your architecture moves large volumes of data between providers or out to the internet, data transfer pricing may be the single most important factor in your aws vs azure vs gcp cost comparison, and it favors Azure for standard egress.

Hidden Costs to Watch

Beyond compute, storage, and transfer, every provider levies a constellation of smaller charges that compound quickly in production. These are the line items that turn a reasonable-looking estimate into an unexpectedly large bill:

• Load balancers: $18–$25/month per balancer across all three providers, plus data processing fees on top.
• NAT gateways: $32–$45/month on AWS and Azure, plus per-GB data processing charges. GCP’s Cloud NAT has a similar cost profile.
• Unattached static IPs: $3–$4/month per IP when not associated with a running instance—on all three providers. Orphaned IPs are a frequent source of waste.
• Managed database backups and snapshots: Charged per GB-month and often retained longer than needed, silently accumulating cost.
• CloudWatch / Azure Monitor / Cloud Logging: Ingestion and retention fees for logs and metrics can balloon if verbose logging is left at default settings.
• Support plans: AWS, Azure, and GCP each offer free basic support, but production-grade support (response-time SLAs, technical account managers) starts at 3–10% of your monthly cloud spend.

None of these appear in headline pricing comparisons, yet collectively they can add 15–25% to your effective cloud bill. They’re documented—not hidden—but easy to miss when you’re focused on instance and storage rates.

How to Track Costs Across All Three

Each provider offers its own native cost tool—AWS Cost Explorer, Azure Cost Management, and Google Cloud Billing reports. These are useful within a single provider’s ecosystem, but they create a fundamental problem for anyone running multi-cloud: you log into three separate consoles, reconcile three different billing taxonomies, and manually aggregate data to understand total spend. By the time you’ve compiled a unified view, the data is already days old.

This is exactly the problem Lytica Costs solves. Instead of juggling native dashboards, Lytica Costs pulls billing data from AWS, Azure, and GCP—plus eight other cloud providers—into a single unified dashboard. Snapshots update every six hours, so you’re never working from stale data. Built-in cost optimization recommendations flag idle resources, oversized instances, and unattached storage across every provider at once. Anomaly detection surfaces unexpected spend spikes before they snowball. Budget alerts notify you the moment a project, team, or account crosses a threshold you define—no matter which provider it’s running on.

For teams managing even a modest multi-cloud footprint, consolidating cost visibility into one place is the difference between catching a $2,000 egress anomaly in hours versus discovering it on next month’s invoice.

Which Provider Is Cheapest? (It Depends)

Any honest aws vs azure vs gcp cost comparison has to acknowledge that there is no universal winner. The cheapest provider depends on your workload profile:

• For compute-heavy, steady-state workloads with 1–3 year commitments: All three converge within a few dollars per month. Pick based on ecosystem fit, not price.
• For bursty, interruptible workloads: Azure spot instances offer the steepest discounts (up to 90%), though AWS and GCP spot pricing is competitive too.
• For storage-heavy workloads: Azure generally has the edge on standard object storage pricing, but watch those per-operation fees.
• For high-egress workloads: Azure is cheapest for standard internet egress; GCP is the most expensive. Architecture decisions (caching, CDN, co-locating data and compute) matter more than provider choice here.
• For Arm-based workloads: Azure offers the largest x86-to-Arm price gap, making it especially attractive for flexible, cost-sensitive compute.
• For automatic discounts without commitment: GCP’s sustained-use discounts apply automatically—no manual Savings Plan configuration required.

The reality is that most organizations end up using more than one provider, whether by design or through acquisitions. When that happens, the question becomes “how do I track and optimize spend across all of them simultaneously?”

Conclusion

The aws vs azure vs gcp cost comparison in 2026 reveals three providers that are closer in price than their marketing suggests—and farther apart in the details that actually determine your bill. Compute rates converge under committed-use discounts. Storage pricing varies by tier and operation count. Data transfer costs diverge meaningfully. And hidden infrastructure fees lurk in every provider’s billing structure, waiting to inflate your spend if you’re not watching.

There is no single cheapest cloud. There’s only the cheapest cloud for your specific workloads—and that answer changes as your architecture evolves. The winning strategy isn’t picking one provider and hoping for the best; it’s maintaining continuous, unified visibility into what you’re actually spending across every provider you use.

That’s what Lytica Costs delivers: one dashboard for AWS, Azure, GCP, and eight other providers, with six-hour snapshots, anomaly detection, budget alerts, and actionable optimization recommendations—so you always know where your cloud money is going and what to do about it.

Stop guessing. Start tracking. Visit costs.lytica.us to unify your multi-cloud cost visibility today.