Confidential GPU Pricing: VoltageGPU vs Azure vs AWS Nitro (Real Numbers, April 2026)

I get the same email roughly twice a week: "your H200 price is significantly below Azure's confidential VM rate — what's the catch?" It's a fair question, and it deserves a real answer rather than a sales deflection. So I sat down on April 24, 2026, pulled the actual public rates from Azure, AWS, and our own dashboard, and built the comparison I wish vendors would publish for themselves.

One ground rule: the only fair comparison is GPU + confidential-compute attestation. Comparing a vanilla A100 to a TDX H200 is not a meaningful price comparison; it's a different product. Every line in this post is for a GPU SKU that ships with hardware-rooted attestation enabled.

TL;DR — The Pricing Table

The H200 number is the one that surprises people. We are not 10% cheaper. We are roughly a quarter of the price of Azure's comparable H100 confidential VM — with newer silicon, more memory, and an Intel-signed attestation quote. Below, I'll explain why.

How We Charge Less Without Cutting the Wrong Corner

Three reasons our pricing isn't a trick:

1. No hyperscaler overhead. Azure's confidential VMs aren't just GPUs; you're also paying for a global enterprise sales motion, a compliance team you'll never speak to, and a 24/7 support tier you didn't ask for. That all ends up in the SKU. We don't carry it.
2. Bare metal, fixed markup. Our cost structure is silicon + datacenter + a transparent 1.50× multiplier. There is no virtualization tax to a parent vendor. Margins are tight on purpose — we are competing on price and trust, not just one of them.
3. Newer fleet, denser packing. Hopper and Blackwell amortize confidential overhead better than Ampere or pre-2023 datacenter GPUs. Most hyperscaler CC SKUs are still on H100 because that's where they have inventory. We brought H200 and B200 online faster.

Annual TCO — Real Numbers, Boring Math

A common workload pattern: 8 GPU-hours a day, 5 days a week, ~2,080 hours/year. That's roughly what a small clinical-summarization or contract-review pipeline burns. At those numbers:

# Annual TCO at 8 GPU-hours/day, 5 days/week (~2080 hrs/year).
# Real numbers from April 2026 published rates.

annual_hours = 2080

# H200 TDX, GDPR/HIPAA-grade
voltagegpu_h200 = 3.60 * annual_hours   # $7,488
azure_cc_h100   = 5.60 * annual_hours   # $11,648  (Azure has no H200 CC SKU yet)
aws_p5_nitro    = 6.18 * annual_hours   # $12,854  (P5.48xlarge / 8, est. confidential add-on)

print(f"VoltageGPU H200 TDX : ${voltagegpu_h200:>9,.0f}/yr")
print(f"Azure NCv5 H100 CC  : ${azure_cc_h100:>9,.0f}/yr")
print(f"AWS P5 Nitro (est.) : ${aws_p5_nitro:>9,.0f}/yr")
print()
print(f"Saved vs Azure : ${azure_cc_h100 - voltagegpu_h200:>9,.0f}/yr  ({(1 - voltagegpu_h200/azure_cc_h100):.0%})")
print(f"Saved vs AWS   : ${aws_p5_nitro  - voltagegpu_h200:>9,.0f}/yr  ({(1 - voltagegpu_h200/aws_p5_nitro):.0%})")

Output (approximate, Apr 2026 rates):

• VoltageGPU H200 TDX: $7,488/yr
• Azure NCv5 H100 CC: $11,648/yr
• AWS P5 Nitro (est.): $12,854/yr

Saved versus Azure: ~$4,160/yr (36%). Saved versus AWS: ~$5,366/yr (42%). And those numbers are before Azure's typical "BAA premium" for regulated sectors, which we discuss in the HIPAA piece. With BAA loading, the gap typically widens to 50%+.

It's Not Just Price — It's What You Actually Get

Cheap-but-shoddy is not what we're selling. The deliverable on every confidential pod includes:

• Intel-signed TDX attestation quote on demand — the same artifact a CNIL or HHS auditor would accept as Article 32 / 45 CFR § 164.312 evidence.
• TEE-IO PCIe encryption on H100/H200/B200 (most hyperscaler CC SKUs do not yet expose this).
• EU-pinned regions by default (France, Germany), opt-in US.
• OpenAI-compatible API — drop-in for any existing OpenAI SDK code.
• Per-minute billing with hard credit caps so you can't be surprised by a $3,000 spike.

Where Azure and AWS Genuinely Win (Pratfall, Honest Edition)

Three places I'd still recommend a hyperscaler over us today, and won't insult your intelligence by pretending otherwise:

• You need 50+ adjacent managed services. If your architecture leans on Azure SQL, Cosmos DB, Defender for Cloud, Sentinel, and the kitchen sink, the cost of stitching us into that environment may eat the savings. Stay where the rest of your stack lives.
• Your procurement requires SOC 2 Type II on day one. Hyperscalers have it. We're mid-audit, due Q3 2026. If a non-negotiable line in your RFP says "SOC 2 Type II," we're the wrong vendor until then.
• You want global edge inference under 50ms. Hyperscalers have hundreds of POPs. We have ~15 datacenter regions. For most batch and async LLM workloads this is irrelevant; for ultra-low-latency edge AI it is not.

For a typical regulated-industry team running async inference, summarization, document review, or coding-assist? The math says try us first, fall back to Azure if something breaks.

Who Should Care About These Numbers

• CTOs and AI leads in regulated sectors who keep getting Azure CC quotes back from their finance team and choking on them.
• FinOps and procurement teams running GPU cost-rationalization exercises across portfolios.
• AI startups selling into healthcare, legal, or fintech where confidential compute is on every customer's checklist.
• Solo builders who want a real H200 with a real attestation quote for $3.60/hr instead of a $14/hr enterprise quote with a 6-week procurement cycle.

If that sounds like you, three places to go next:

• Live prices — updated every 5 minutes from the provider, no marketing markup.
• Pricing page — the raw markup math, written down.
• Browse confidential GPUs — pick a pod, deploy in under 60 seconds.

FAQ