Quick Answer: Azure Confidential Computing H100 instances cost $14/hr with 6-12 months of DIY setup. VoltageGPU's Intel TDX H200 nodes cost $3.60/hr, same hardware encryption, EU-based, deploy in 60 seconds. That's 74% cheaper for actual confidential inference, not just raw VMs you still have to build yourself.
I spent 3 hours in Azure Portal trying to provision a Confidential H100 cluster. Three hours of ARM templates, tenant approvals, and quota requests. Gave up. Called a friend who actually finished the setup. His bill: $14/hr for the VM, plus $2,400/mo for the engineer keeping it running. Six months later, he still doesn't have hardware attestation wired to his inference pipeline.
This is the gap nobody talks about. Azure sells you encrypted hardware. You still build everything else.
Why Confidential Computing Stopped Being Optional
In January 2025, ShinyHunters threatened to leak data from 560,000 students. Cloudflare cut 20% of staff. The pattern is obvious: centralized infrastructure is a target, and "trust us" stopped working as a security model.
Regulators noticed. GDPR Article 25 now mandates data protection by design. DORA and NIS2 require financial institutions to prove their AI processing happens in verifiably isolated environments. Not policies. Proof.
Intel TDX (Trust Domain Extensions) is that proof. The CPU encrypts memory with AES-256 at runtime. A hardware-signed attestation report proves your code ran in a real enclave, not a mocked environment. The host operator, us, Azure, anyone, sees ciphertext only.
The problem? Getting it to actually run your models.
Azure Confidential Computing: What You Actually Get
Microsoft's offering is technically correct. Confidential H100 VMs. Intel TDX enabled. Full stop.
What they don't provide:
- Pre-configured inference stack (PyTorch, vLLM, TGI)
- Model serving with attestation verification
- GDPR Article 25 documentation out of the box
- Hardware in the EU (most SKUs are US-East, US-West, or Southeast Asia)
You rent silicon. The 6-12 month build is on you.
| What You Need | Azure Confidential H100 | VoltageGPU TDX H200 |
|---|---|---|
| Base compute | $14/hr | $3.60/hr |
| Pre-built inference stack | No | Yes (vLLM + TDX attestation) |
| Time to first inference | 6-12 months DIY | ~60 seconds |
| Hardware location | US/Asia mostly | EU (France) |
| GDPR Art. 25 documentation | Build yourself | Native, DPA available |
| Hardware attestation API | Manual integration | Automatic, CPU-signed |
| SOC 2 certification | Yes | No |
That last row matters. Azure wins on enterprise certifications. If your procurement team requires SOC 2 Type II, Azure is your only option today. We're not pretending otherwise.
What Intel TDX Actually Does (And Doesn't)
I keep seeing "military-grade encryption" in marketing. Here's the actual mechanics.
TDX creates a Trust Domain, a hardware-isolated execution environment with its own memory encryption key. The CPU's Memory Encryption Engine (MEE) encrypts all RAM traffic with AES-256-XTS. The TDX Module, Intel's signed firmware, manages the boundary. On boot, the CPU generates an attestation report signed with Intel's root key. This report includes:
- Measurement of the initial code (your model + inference stack)
- Security version numbers of TDX firmware
- Whether debug mode is disabled
You verify this report against Intel's quoting enclave. If it matches, you know your data ran on genuine Intel silicon with no tampering. Not "probably." Cryptographically.
The catch? TDX adds 3-7% latency overhead. Our benchmarks show 5.2% on average for Llama-3.3-70B inference at 120 tok/s. For most compliance use cases, that's noise. For high-frequency trading, it matters.
Real Numbers: Running Confidential Inference
We tested Qwen2.5-72B inside TDX on H200 vs. bare H200. Same prompt batch, same temperature.
| Metric | Bare H200 | TDX H200 | Overhead |
|---|---|---|---|
| TTFT (time to first token) | 718ms | 755ms | +5.2% |
| Throughput | 126 tok/s | 120 tok/s | -4.8% |
| Cost/hr | $3.60 | $3.60 | $0 (same price) |
| Hardware attestation | No | Yes | , |
Same price because we don't charge extra for TDX. The encryption is the product, not an upsell.
For comparison, running the same model on Azure's non-confidential H100 (not even the confidential tier) costs roughly $4.35/hr at spot rates. You pay more for less isolation, and you're still in US East.
The EU Angle Nobody Talks About
GDPR Article 44 (data transfers) is about to get teeth. The EU-US Data Privacy Framework survived its first review, but Schrems III is already being drafted. Forward-looking legal teams aren't betting on adequacy decisions lasting.
Running inference under an EU legal entity, on hardware you can attest yourself, isn't preference. It's preparation.
VoltageGPU operates from France (SIREN 943 808 824). Intel TDX attestation proves the hardware state. GDPR Article 25 documentation is generated automatically. A Data Processing Agreement is available on request, not "contact sales and wait," but actually available.
This is the azure confidential computing alternative that doesn't require you to become a cloud infrastructure company.
What Running This Actually Looks Like
No custom SDK. Standard OpenAI client, different base URL:
from openai import OpenAI
client = OpenAI(
base_url="https://api.voltagegpu.com/v1/confidential",
api_key="vgpu_YOUR_KEY"
)
response = client.chat.completions.create(
model="contract-analyst",
messages=[{"role": "user", "content": "Review this NDA clause: 'Recipient may disclose Confidential Information to employees on a need-to-know basis...'"}]
)
print(response.choices[0].message.content)
The contract-analyst model runs Qwen2.5-72B inside a TDX enclave on H200. The attestation report is available via /v1/confidential/attestation if your compliance team needs verification. Zero data retention, the prompt leaves no trace after the response completes.
Or use curl if you're testing:
curl https://api.voltagegpu.com/v1/confidential/chat/completions \
-H "Authorization: Bearer vgpu_YOUR_KEY" \
-d '{"model":"contract-analyst","messages":[{"role":"user","content":"Analyze this clause for GDPR Article 28 compliance..."}]}'
What I Didn't Like (Honest Limitations)
-
No SOC 2 certification. Our compliance model is GDPR Article 25 + Intel TDX attestation + DPA. If your procurement requires SOC 2 Type II, we can't check that box yet. Azure can.
-
TDX adds 3-7% latency overhead. For real-time applications sensitive to every millisecond, this matters. Most document analysis, compliance review, and legal workflows don't notice.
-
Cold start 30-60s on Starter plan. The $349/mo tier shares a pool. First request after idle waits for warm-up. Pro tier $1,199/mo has dedicated allocation.
-
PDF OCR not supported. Text-based PDFs work fine. Scanned documents need pre-processing elsewhere.
The Honest Cost Breakdown
| Scenario | Azure Confidential H100 | VoltageGPU TDX H200 |
|---|---|---|
| 1 month, 8hr/day inference | $3,360 + engineer time | $864 |
| 6-month pilot build | $20,160 + $14,400 engineer | $5,184 |
| GDPR documentation | Self-generated | Auto-generated |
| Hardware attestation | Manual integration | Automatic |
The 74% compute savings assume you value engineer time at $0. If you're realistic, the gap is larger.
When Azure Still Makes Sense
- You need SOC 2 Type II today
- You're already deep in ARM templates and Azure DevOps
- You have 6-12 months before production