AWS vs Azure vs GCP: Which Cloud Is Actually Cheaper for Your Workload?

“Which cloud is cheapest” is the wrong question for an AWS vs Azure vs GCP cost comparison, and it’s why so many of them end up useless. The right question is which cloud is cheapest for your specific workload shape — because the pricing gap between providers can flip by 20–40% depending on whether you’re comparing steady-state compute, bursty batch jobs, or data-heavy analytics. Here’s how the cloud pricing comparison actually breaks down, by workload type rather than by provider.

AWS vs Azure vs GCP Cost for Steady-State Compute

For predictable, always-on workloads, the comparison comes down to committed use discounts rather than on-demand rates, since almost nobody runs steady-state compute at on-demand pricing.

	AWS	Azure	GCP
Discount model	Savings Plans	Reserved Instances	Sustained-use (automatic) + Committed-use
Flexibility	High — flexible across instance families and regions	Lower — less flexible to switch instance types mid-term	High — sustained-use applies automatically, no upfront commitment needed
Best for	Fleets whose instance composition changes over time	Predictable, long-term stable workloads willing to commit upfront	Teams that want a competitive rate without a procurement process
Effective rate after discounts	Competitive, close to GCP	Typically requires a longer or larger commitment to match	Often the simplest path to a low effective rate

For workloads that run 24/7 with a predictable shape, GCP and AWS tend to land closest together after discounts are applied; Azure typically requires a longer or larger commitment to reach the same effective rate.

AWS vs Azure vs GCP Cost for Bursty and Batch Workloads

Spot instance pricing is where the providers diverge most:

	AWS Spot	GCP Preemptible/Spot	Azure Spot
Market depth	Deepest and most liquid	Competitive	Least mature of the three
Interruption handling	Requires careful handling	More predictable interruption notice	Less consistent availability across regions
Typical fit	Fault-tolerant batch workloads chasing the deepest discount	Workloads that want lower engineering overhead around interruptions	Workloads with more availability flexibility

For workloads that can tolerate interruption, AWS or GCP spot pricing usually wins over Azure on both cost and reliability of the discount.

Storage, Cloud Egress Costs, and Data Transfer

This is where an AWS vs Azure vs GCP cost comparison surprises people most — compute pricing gets all the attention, but cloud egress costs and storage tiering often decide the real winner:

• All three providers charge for egress, but the free tiers and pricing tiers differ enough that a data-heavy workload can see meaningfully different bills depending on provider.
• GCP’s network pricing has historically been more transparent with fewer regional pricing tiers to navigate.
• AWS and Azure both offer cheaper storage classes for cold data, but the retrieval costs and minimum storage durations differ enough to change the effective cost for workloads with unpredictable access patterns.

Why the “Cheapest Cloud Provider” Answer Changes Every Year

Provider pricing changes frequently, and discount structures get revised. A comparison that was accurate a year ago may not hold today – there is no single cheapest cloud provider that stays true across workload types or stays fixed year over year. The workloads that benefit most from a rigorous comparison are the ones large enough that a 10-15% pricing gap translates into real budget impact – which is most workloads once they’re past the early-stage/testing phase.

The Only Reliable Way to Settle AWS vs Azure vs GCP Cost for Your Workload

Public pricing pages compare list prices. Your actual cost depends on your specific instance mix, commitment level, data transfer patterns, and discount eligibility – none of which a generic comparison article can calculate for you. For the tactical steps to apply once you know where your spend actually sits, see the cloud cost optimization checklist, and for the broader discipline this comparison feeds into, see multi-cloud cost management.

CloudPi, a multi-cloud cost management and governance platform, tracks real spend across AWS, Azure, and GCP side by side, so instead of guessing which provider is cheaper in the abstract, you can see exactly what an equivalent workload is costing you on each cloud you’re already running – and make the provider decision on your actual numbers.

Frequently Asked Questions