Burn provides a flexible, efficient, and portable tensor library for building deep learning applications.
Open source
24 alternativesdstack
dstack provides an open framework for confidential AI computing and deployments.
About dstack
dstack is an open-source framework for running AI containers inside confidential virtual machines based on Intel TDX or AMD SEV-SNP, with support for NVIDIA Confidential Computing on H100 and Blackwell GPUs. It runs existing Docker Compose files, encrypts network traffic and disk storage by default, and provides workload identity and attestation for verification.
Self-hosted deployment uses TDX machines, while AMD SEV-SNP hosts require an SNP-capable guest image that includes digest.txt. The mkosi OS backend is the current option; the Yocto backend is deprecated and kept only to rebuild existing images.
Key features
- Runs containers inside Intel TDX or AMD SEV-SNP confidential VMs
- Supports NVIDIA Confidential Computing on H100 and Blackwell GPUs
- Deploys existing docker-compose.yaml without code changes
- Encrypts network traffic and disk storage by default
- Provides cryptographically verifiable workload identity and attestation
- Derives per-app keys inside TEE, not exposed to operators
Best for: Developers deploying AI applications that require hardware-isolated execution and verifiable workloads.
Good for
- Works with existing Docker Compose workflow without code changes
- Supports bare metal, Phala Cloud, GCP Confidential VMs, and AWS Nitro Enclaves
- Provides reproducible OS builds and attestation for verification
Watch out for
- AMD SEV-SNP deployment requires an SNP-capable guest image with digest.txt
- Yocto OS backend is deprecated and not for new work
- Development without TEE hardware requires a development image with no-TEE mode
dstack at a glance
- Website
- github.com/Dstack-TEE/dstack
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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dstack FAQ
How can I try dstack without deploying it?
Chat with LLMs running in TEE at chat.redpill.ai and select the shield icon to check attestations from Intel TDX and NVIDIA GPUs.
How do I deploy my own application?
Deploy to a self-hosted TDX machine with the dstackup install to dstack deploy workflow, or use Phala Cloud for managed infrastructure.
Can I develop without TEE hardware?
Yes, use a development image with no-TEE mode and swtpm.
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