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The Microsoft Azure alternative priced by the whole market

Microsoft Azure sells GPU compute through its N-series virtual machines, with strong enterprise and hybrid-cloud integration. GPU.ai takes the other approach: one account that prices 12+ clouds on every launch and passes the raw rate through at zero markup.

At a glance

Microsoft Azure vs GPU.ai

A fair read of both sides — their genuine strengths, the trade-offs, and what an aggregated market does differently.

Microsoft Azure

Strengths

  • +First-class integration with the Microsoft enterprise stack
  • +Broad global region coverage for data-residency requirements
  • +Access to OpenAI-adjacent managed AI services

Trade-offs

  • GPU list prices sit at the top of the market
  • Quota and capacity constraints on popular SKUs are common
  • Committed-use agreements are where the real discounts hide

GPU.ai

The aggregator model

  • Every launch is routed to the cheapest of 12+ clouds with live stock
  • Zero markup — the provider's raw rate is the price you pay
  • Per-second billing from SSH-ready to terminate
  • 30+ GPU models, from budget consumer cards to flagship training silicon
  • One account, one API, one CLI across the whole market
Live pricing

What GPUs cost on GPU.ai right now

Live per-GPU floor prices across our aggregated fleet, next to Microsoft Azure's public on-demand list rates where they sell the same model.

GPUVRAMGPU.ai / GPU / hrMicrosoft Azure listStock
RTX A400016 GB$0.070Not sold35 available
RTX 308010 GB$0.085Not sold21 available
V10016 GB$0.105Not sold5 available
RTX 309024 GB$0.115Not sold67 available
RTX 408016 GB$0.130Not sold8 available
RTX 508016 GB$0.150Not sold32 available
RTX A450020 GB$0.190Not sold8 available
RTX A500024 GB$0.233Not sold13 available
RTX 2000 Ada16 GB$0.240Not sold8 available
RTX 409024 GB$0.270Not sold176 available
RTX 509032 GB$0.295Not sold69 available
L424 GB$0.320Not sold33 available
RTX PRO 450032 GB$0.340Not sold49 available
A4048 GB$0.440Not sold52 available
RTX A600048 GB$0.450Not sold50 available
L4048 GB$0.575Not sold156 available
A100 40GB40 GB$0.610Not sold26 available
RTX 6000 Ada48 GB$0.650Not sold64 available
L40S48 GB$0.790$2.50251 available
A100 80GB80 GB$0.935$4.1082 available
RTX PRO 600096 GB$1.69$5.50204 available
H100 SXM80 GB$1.74$12.2950 available
H100 PCIe80 GB$1.87Not sold9 available
H100 NVL94 GB$2.59Not sold21 available
H200 SXM141 GB$3.59$12.9966 available
H200 NVL141 GB$3.60Not sold5 available
B200192 GB$5.32Not sold12 available

How this comparison works

GPU.ai prices are live per-GPU floor rates from our aggregated fleet, normalized per GPU per hour, billed per second, with zero markup on the provider's raw rate. Microsoft Azure figures are their public on-demand list rates for the closest equivalent SKU — never spot, reserved, or committed-use discounts. We only show models with launchable stock. Last updated 2026-08-17; this page refreshes hourly.

Honest verdict

Which should you pick?

Stay with Microsoft Azure if…

  • Your organization runs on Microsoft enterprise agreements
  • You need Azure-specific managed AI services

Switch to GPU.ai if…

  • You just need GPUs, not the enterprise wrapper priced into every hour
  • You want per-second billing instead of committed-use math
FAQ

Switching from Microsoft Azure

Is GPU.ai a good Microsoft Azure alternative?

GPU.ai takes a different approach: instead of running one fleet, it prices the whole GPU market on every launch and routes you to the cheapest provider with live stock, at the provider's raw rate with zero markup. If Microsoft Azure's strengths — first-class integration with the microsoft enterprise stack — are not the thing you're paying for, an aggregated market usually wins on price and availability.

How does GPU.ai pricing compare to Microsoft Azure?

GPU.ai publishes its live per-GPU floor price for every model it carries — currently from $0.070/GPU/hr at the low end. Prices are normalized per GPU per hour and billed per second, and the comparison table on this page is refreshed hourly from live fleet data.

How hard is it to switch from Microsoft Azure to GPU.ai?

Launches are standard SSH instances with your keys, so most workflows move without changes: pick a GPU, launch, rsync your data, run. There are no commitments to unwind and no minimum spend — you can trial a single instance for a few cents before moving anything.

When should I stay with Microsoft Azure?

Honestly: your organization runs on microsoft enterprise agreements, or if you need azure-specific managed ai services. This page's job is a fair comparison, not a hard sell — the live price table above is the argument that matters.