Comparison
dstack vs pytorch-lightning
Verdict
Pick dstack if vendor-agnostic AI workload orchestration tool supports GPU providers like NVIDIA and AMD across cloud, Kubernetes, and bare metal; pick pytorch-lightning if pyTorch Lightning scales PyTorch models across GPUs with minimal code changes.
Markdown twin · dstack alternatives · pytorch-lightning alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | dstack | pytorch-lightning |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No published findings from this source as of 2026-07-11 As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- dstack
- Vendor-agnostic orchestration for AI workloads
- pytorch-lightning
- Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Stars
- dstack
- 2.2k
- pytorch-lightning
- 31k
Forks
- dstack
- 240
- pytorch-lightning
- 3.8k
Open issues
- dstack
- 61
- pytorch-lightning
- 1.1k
Language
- dstack
- Python
- pytorch-lightning
- Python
Adopt for
- dstack
- Vendor-agnostic AI workload orchestration tool supports GPU providers like NVIDIA and AMD across cloud, Kubernetes, and bare metal.
- pytorch-lightning
- PyTorch Lightning scales PyTorch models across GPUs with minimal code changes.
Persona
- dstack
- -
- pytorch-lightning
- -
Runtime
- dstack
- -
- pytorch-lightning
- -
License
- dstack
- MPL-2.0
- pytorch-lightning
- Apache-2.0
Last pushed
- dstack
- Jul 24, 2026
- pytorch-lightning
- Aug 3, 2026
Categories
- dstack
- AI Agents, Inference & Serving, Model Training
- pytorch-lightning
- Inference & Serving, Model Training
Trust and health
Open issues (now)
- dstack
- 61
- pytorch-lightning
- 1.1k
OSV dependency advisories
- dstack
- No lockfile (source not queried)
- pytorch-lightning
- No published findings from this source as of 2026-07-11
Full report
- dstack
- Trust report
- pytorch-lightning
- Trust report
Choose dstack if…
- License: dstack is MPL-2.0, pytorch-lightning is Apache-2.0.
- Tags unique to dstack: agent-skills, agentic-orchestration, amd, cloud.
- Also covers AI Agents.
- If your project requires support for multiple hardware vendors such as NVIDIA, AMD, TPU, or Tenstorrent
When NOT to use dstack
- When sticking to single-vendor solutions where tightly integrated proprietary tools are preferred
- If the project strictly avoids open-source components with Mozilla Public License (MPL-2.0)
Choose pytorch-lightning if…
- License: pytorch-lightning is Apache-2.0, dstack is MPL-2.0.
- Tags unique to pytorch-lightning: ai, artificial-intelligence, data-science, deep-learning.
- Scalable ML model training with consistent API across single to multiple GPUs
When NOT to use pytorch-lightning
- For lightweight models requiring minimal configuration or manual control over model distribution
- Projects that target environments without access to multi-GPU setups and do not require scalability features
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (dstackai/dstack) · observed Jul 24, 2026
- GitHub forks (dstackai/dstack) · observed Jul 24, 2026
- Last push (dstackai/dstack) · observed Jul 24, 2026
- License file (MPL-2.0) · observed Jul 24, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Lightning-AI/pytorch-lightning) · observed Aug 3, 2026
- GitHub forks (Lightning-AI/pytorch-lightning) · observed Aug 3, 2026
- Last push (Lightning-AI/pytorch-lightning) · observed Aug 3, 2026
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: dstack 2.2k · pytorch-lightning 31k (synced Jul 24, 2026).
Common questions
- What is the difference between dstack and pytorch-lightning?
- dstack: Vendor-agnostic orchestration for AI workloads. pytorch-lightning: Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.. See the comparison table for live GitHub stats and shared categories.
- When should I choose dstack over pytorch-lightning?
- Choose dstack over pytorch-lightning when License: dstack is MPL-2.0, pytorch-lightning is Apache-2.0; Tags unique to dstack: agent-skills, agentic-orchestration, amd, cloud; Also covers AI Agents; If your project requires support for multiple hardware vendors such as NVIDIA, AMD, TPU, or Tenstorrent.
- When should I choose pytorch-lightning over dstack?
- Choose pytorch-lightning over dstack when License: pytorch-lightning is Apache-2.0, dstack is MPL-2.0; Tags unique to pytorch-lightning: ai, artificial-intelligence, data-science, deep-learning; Scalable ML model training with consistent API across single to multiple GPUs.
- When should I avoid dstack?
- When sticking to single-vendor solutions where tightly integrated proprietary tools are preferred If the project strictly avoids open-source components with Mozilla Public License (MPL-2.0)
- When should I avoid pytorch-lightning?
- For lightweight models requiring minimal configuration or manual control over model distribution Projects that target environments without access to multi-GPU setups and do not require scalability features
- Is dstack or pytorch-lightning more popular on GitHub?
- pytorch-lightning has more GitHub stars (31,267 vs 2,192). Stars measure visibility, not whether either tool fits your constraints.
- Are dstack and pytorch-lightning open source?
- Yes - both are open-source projects on GitHub (dstack: MPL-2.0, pytorch-lightning: Apache-2.0).
- Where can I find alternatives to dstack or pytorch-lightning?
- GraphCanon lists graph-backed alternatives at dstack alternatives and pytorch-lightning alternatives (dstack markdown twin, pytorch-lightning markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, dstack or pytorch-lightning?
- dstack: Very active. pytorch-lightning: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for dstack and pytorch-lightning?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dstack trust report; pytorch-lightning trust report.