Intel TDX vs AMD SEV-SNP for Confidential AI: A 2026 Technical Comparison

I get this question every week from CTOs picking a confidential-AI substrate: "why TDX and not SEV-SNP?" The honest answer is that both work, both seal a VM against a privileged operator, and both will be acceptable to most regulators. But they are not interchangeable on the dimensions that actually matter for AI: GPU integration, attestation tooling, and the maturity of the audit story you can hand to a notified body.

This post is the comparison I wish someone had written for me when we made this call at VoltageGPU. It is opinionated. The other path (SEV-SNP) is legitimate; we picked TDX because the trade-offs lined up for the regulated-industries customers we serve.

Threat model: what each technology protects against

Strip the marketing and both technologies answer the same question: can a privileged operator on the host (hypervisor admin, SRE, hardware tech with physical access) read or tamper with my workload memory?

• Intel TDX (Trusted Domain Extensions) creates a Trust Domain, a VM whose memory is encrypted with AES-256-XTS keys held by the CPU, inaccessible to the hypervisor or host OS. The CPU also enforces page-mapping isolation so the host cannot re-map physical pages to read or substitute enclave memory.
• AMD SEV-SNP (Secure Encrypted Virtualization, Secure Nested Paging) is the third-generation evolution of AMD’s confidential VM technology. It encrypts guest memory with a per-VM key and adds protections against the data corruption, replay, and re-mapping attacks that SEV and SEV-ES did not address.

On the CPU-only attack surface, the two are roughly equivalent. Both stop a malicious operator from reading RAM. Neither stops you from being sloppy inside your own enclave (e.g., logging plaintext to disk).

Where they diverge: the GPU story

Confidential AI is not just about CPU memory. It is about whether the model weights, KV cache, and activations sitting in GPU HBM are protected, and whether the PCIe link between CPU and GPU is encrypted in transit.

NVIDIA Confidential Computing (introduced on Hopper, expanded on Blackwell, fully featured on the upcoming Vera Rubin) provides a GPU-side TEE that pairs with a host TEE-VM. The host TEE proves the CPU side is sealed; the NVIDIA attestation proves the GPU side is sealed; the TEE-IO / trust-domain GPU isolation encryption proves the bus between them is sealed.

Practically, in April 2026:

• TDX + NVIDIA H100 / H200 / B200 is the integration NVIDIA, Microsoft, Google, and we (VoltageGPU) all document and ship as the primary path. Google Cloud A3 High (Intel TDX + H100) and VoltageGPU Confidential VMs; Azure's confidential GPU series (NCC H100 v5) runs AMD SEV-SNP instead, and its Intel TDX DCe family carries no GPU.
• SEV-SNP + NVIDIA H100 works at the technical level but is materially less documented in cloud catalogues. If you want to combine SEV-SNP with a confidential GPU in production, you are very likely doing the integration yourself.

If your workload is CPU-only confidential inference, this difference does not bite. If your workload is the actually-interesting case, large LLM inference or training on sensitive data on H200, this is the difference that drove our choice.

Attestation: the part regulators actually care about

A "confidential" claim is worth nothing without verifiable, third-party-rooted proof. Both technologies generate attestation quotes. The differences are in the verification chain.

• TDX attestation chains to Intel’s Provisioning Certification Key (PCK) and ultimately to Intel’s root CA. The DCAP (Data Center Attestation Primitives) tooling is open-source, well-documented, and what every TDX-aware cloud provider uses. A notified body, internal auditor, or CISO can verify a TDX quote with off-the-shelf tooling against a known PKI.
• SEV-SNP attestation chains to AMD’s VCEK (Versioned Chip Endorsement Key) and AMD’s root. It is equally cryptographically sound. The tooling, however, has historically lagged Intel’s in third-party documentation, tutorials, and ecosystem libraries. This is closing rapidly in 2026 but is still not at parity.

For our regulated-industries customers, the question is not "can I produce a quote?" but "can my auditor verify it without learning a new PKI and a new toolchain?" In April 2026, that pushes us toward TDX. See our step-by-step attestation verification guide for the actual mechanics.

Regulator and auditor acceptance

Both technologies are accepted by regulators as technical measures under GDPR Article 32 and as Article 15 evidence under the EU AI Act. We have not seen a regulator distinguish between them in writing.

What we have seen, in actual customer DPIA and AI Act conformity discussions, is a clear preference for TDX-rooted evidence on two grounds:

• The Intel DCAP verification path has more public documentation, more open-source libraries, and more existing notified-body familiarity. Less chance of a six-week back-and-forth on "how do we verify this signature?"
• Cloud-provider documentation. Microsoft Azure publishes a comprehensive confidential computing assurance pack rooted in TDX evidence; that document tends to show up in customer compliance binders, which makes the TDX evidence pattern familiar to auditors before they even see ours.

None of this means SEV-SNP fails an audit. It means the path of least resistance, in 2026, runs through TDX. For the legal-side of this discussion, see our GDPR & AI piece and the EU AI Act compliance article.

When SEV-SNP is the right answer

I would pick SEV-SNP over TDX in three scenarios:

• You are CPU-only. No confidential GPU in scope. Just regulated-data processing in a sealed VM. Then the CPU you pick comes down to ecosystem fit, price, and your existing AMD/Intel relationships.
• You are deep in the AMD ecosystem already. EPYC Bergamo or Genoa fleets where adding TDX hosts means adding a parallel Intel fleet you do not want.
• Your workloads are not under EU AI Act high-risk Annex III. The attestation-evidence asymmetry matters most when a notified body is in the loop. For internal-only or non-high-risk workloads, the choice flattens out considerably.

Bottom line

TDX and SEV-SNP solve the same problem. They are not equivalent for confidential AI in 2026. TDX has the documented NVIDIA confidential-GPU integration, the more mature attestation-verification ecosystem, and the path of least resistance through regulator review.

That is why we run TDX at VoltageGPU. It is not the only correct choice. It is the choice that makes the customer’s next conversation, with their CISO, their DPO, or their notified body, shorter.

Related reading

• What Intel TDX actually does: the deep-dive
• How to verify your LLM is actually running in a TEE
• EU AI Act August 2026: high-risk LLM compliance
• GDPR & AI in 2026: why a DPA is not enough
• Confidential GPU pricing, VoltageGPU vs Azure vs AWS

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