Tinfoil
Verifiably private AI – trust the hardware, not the pinky-promises.
Tinfoil delivers on its promise of verifiable AI privacy, but the performance overhead (~10%) and technical complexity limit it to serious enterprises and researchers. If you need cryptographic proof for compliance, it's one of the few options; for casual privacy, simpler tools suffice.
- Developers building AI applications where data never leaves a verifiable enclave
- Enterprises needing SOC 2/GDPR compliance for AI inference
- Researchers auditing frontier model weights without exposing them
- Organizations requiring private chat with cryptographic attestation
- Users wanting a free conversational AI with no privacy overhead
- Projects sensitive to ~10% performance overhead on inference
- Non-technical users who can't configure attestation and Docker
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Skip Tinfoil if you need a free or low-latency AI chat without the ~10% performance overhead and the complexity of setting up TEE attestation.
Going past the Chat plan's 2M tokens/hour fair-use limit may result in throttling during peak demand, though no overage fee is explicitly stated.
Tinfoil's pricing ($20/month for Private Chat, usage-based API, $20/month + usage for Containers) fits developers and enterprises that need verifiable privacy, but is more expensive than standard ChatGPT Pro ($20/month) without the attestation. For compliance-heavy teams, the premium is justified; for casual use, it's overkill.
In short
Tinfoil — Verifiably private AI – trust the hardware, not the pinky-promises. Best for Developers building AI applications where data never leaves a verifiable enclave, Enterprises needing SOC 2/GDPR compliance for AI inference, Researchers auditing frontier model weights without exposing them. Plans from $20/mo.
What's new in Tinfoil
Checked 12 days agoAcross the latest 5 updates: 1 launch, 2 changelog entries and 2 news mentions.
How does NVIDIA Confidential Computing impact inference and training performance?
First public benchmarks of confidential computing overhead on NVIDIA Blackwell for inference and training.
Towards Search, Memory, and More
Announced semantic search and cross-chat memory infrastructure coming to Tinfoil Chat with privacy guarantees.
Auditing a Frontier Model Without Seeing its Weights
Pour Demain used Tinfoil Containers to run gray-box interpretability evals on a 744B model inside enclaves.
Supply Chain Security - Part 1
Tinfoil's approach to supply chain security for client-side code and build infrastructure.
Introducing Tinfoil Containers
Deploy app backends, training pipelines, or proprietary models with verifiably private AI services.
Viability Score
How likely is Tinfoil to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Hardware secure enclave (TEE) execution with NVIDIA Blackwell
- Cryptographic attestation of code and model integrity
- Open-source SDK for attestation verification
- Browser-native verification stack (Sigstore, TUF)
- Private Chat with end-to-end encrypted conversations
- Private Inference API (OpenAI-compatible)
- Tinfoil Containers for any Dockerized workload
- Multi-GPU support
- Private web search with zero query visibility
- Encrypted chat backups and multi-device sync
- Conversation sharing without exposing content
- SOC 2 compliance
- Support for custom models (qwen3-coder-480B, gpt-oss-120b)
- Semantic search and cross-chat memory (infrastructure groundwork)
- Less than 10% performance overhead on production workloads
About Tinfoil
Tinfoil is a confidential computing platform that runs AI workloads inside hardware secure enclaves (TEEs) with cryptographic attestation. It offers three main products: Private Chat ($20/month) — a ChatGPT-like interface with end-to-end privacy, multi-modal AI, web search, and iOS support; Private Inference API (usage-based) — an OpenAI-compatible API for building AI applications with verifiable enclaves; and Tinfoil Containers ($20/month + usage) — run any Docker image in a TEE with your own models. It uses NVIDIA Blackwell GPUs with under 10% performance overhead, supports custom models like qwen3-coder-480B and gpt-oss-120b, and is SOC 2 compliant. The platform is fully open-source and auditable, with browser-native verification (Sigstore, TUF). Recent updates include semantic search and cross-chat memory infrastructure for Chat, and a case study where Pour Demain audited a 744B model without seeing its weights. Tinfoil is distinct from anonymizing proxies by providing cryptographic proof that data never leaves the enclave. It's ideal for developers, enterprises, and researchers needing verifiable privacy for sensitive data.
Behind the Verdict
Tinfoil stands out as a rare verifiable privacy layer for AI workloads, built on hardware TEEs with open-source attestation. Its three product lines cover chat, API inference, and custom containers, giving you flexibility from simple private chat to running your own models with cryptographic proof. The use of NVIDIA Blackwell GPUs and sub-10% overhead makes it viable for production, though you'll feel that overhead on latency-sensitive tasks. The open-source SDK and browser-native verification stack are major trust differentiators — you can actually verify what code ran. However, the tool is complex: setting up attestation, managing Docker images, and understanding TEE nuances require a technical team. The Private Chat fair-use limit of 2M tokens/hour may throttle heavy users, and the Containers pricing (base + usage) can climb. Tinfoil shines in regulated industries (healthcare, finance, government) where compliance demands verifiable data handling, and for frontier model auditors who must not expose weights. It's not for non-technical individuals or teams needing zero-overhead inference.
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Real-world workflow fit
Concrete scenarios for the personas Tinfoil actually fits — and what changes day-one when you adopt it.
Sign up for Private Inference API, read the docs on attestation, and call the OpenAI-compatible endpoint with a flag to enable enclave verification.
Outcome: Chatbot processes PHI inside a verifiable TEE, with cryptographic proof available for audits, satisfying HIPAA requirements.
Subscribe to Private Chat, configure project access, and onboard employees to the web or iOS client with auto-sync and encrypted backups.
Outcome: Team conversations remain confidential with end-to-end encryption and attestation; no data accessible to Tinfoil or third parties.
Use Tinfoil Containers to deploy an auditor's eval script inside a TEE alongside the model weights (e.g., 744B parameter model), then verify attestation logs.
Outcome: Gray-box evaluation completed without exposing the model's weights to the auditor, with cryptographic proof of exactly what ran.
Use Cases
- Deploy a private ChatGPT alternative for internal company use with verifiable data handling.
- Build an AI application that processes customer data under HIPAA/GDPR using enclave attestation.
- Audit a frontier model's behavior without exposing proprietary weights to the auditor.
- Run sensitive data analytics pipelines in a secure enclave with cryptographic proof of integrity.
- Fine-tune a model on confidential datasets using Tinfoil Containers and private post-training infrastructure.
Models Under the Hood
as of 2026-07-15
Limitations
- Performance overhead less than 10% in production workloads.
- The Private Chat plan imposes a fair-use policy and usage may be throttled during peak demand; it has a limit of 3M tokens per hour (not 2M).
- Tinfoil Containers pricing includes a monthly base fee plus usage charges.
as of 2026-07-05
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Tinfoil tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Private Chat
$20/month
Ideal for
Solo professionals and small teams needing a private, verifiable AI chat assistant with web search and multimodal support.
What this tier adds
Starting tier: a ChatGPT-like interface with end-to-end encryption and attestation, capped at 2M tokens/hour.
Private Inference API
Usage-based pricing
Ideal for
Developers building AI applications that require verifiable enclave inference with an OpenAI-compatible API.
What this tier adds
Usage-based pricing with custom model support and multi-GPU, compared to the fixed $20/month Chat tier.
Tinfoil Containers
$20/month + usage
Ideal for
Teams running custom Dockerized AI workloads or proprietary models that need verifiable TEE execution with flexible GPU resources.
What this tier adds
Adds ability to run any Docker image in a TEE with your own models, beyond the Chat and API offerings; $20/month + usage.
Enterprise
Contact for pricing
Ideal for
Large organizations requiring dedicated support, custom SLAs, on-premise deployment, and advanced compliance configurations.
What this tier adds
Contact-based pricing for tailored features beyond the self-serve Chat, API, and Containers plans.
Where the pricing makes sense
The company stage and team size where Tinfoil's pricing actually pencils out — and where peers do it cheaper.
Tinfoil's pricing ($20/month for Private Chat, usage-based API, $20/month + usage for Containers) fits developers and enterprises that need verifiable privacy, but is more expensive than standard ChatGPT Pro ($20/month) without the attestation. For compliance-heavy teams, the premium is justified; for casual use, it's overkill.
Setup time & first value
How long it actually takes to get something useful out of Tinfoil — broken out by persona, not the marketing-page minute.
Developers can get the Private Inference API running in under an hour with the OpenAI-compatible endpoint and attestation SDK. Private Chat is instant via browser. Tinfoil Containers requires setting up a Docker image and attestation configuration, typically 1-2 hours for first deployment.
Switching to or from Tinfoil
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From ChatGPT or OpenAI API: Tinfoil's Private Chat is a drop-in alternative; the Private Inference API uses OpenAI-compatible endpoints, so you can switch clients with minimal code changes.
- ↗To a local AI setup (e.g., Ollama, local LLMs): Export your chat history and models; Tinfoil's open-source SDK and container images are portable but require TEE hardware to replicate the attestation guarantees.
Integrations
Resources & Guides
Official links
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Common stack mates teams adopt alongside Tinfoil, with the specific reason each pairing earns its keep.
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