⚡️ Lightning AI
@lightning-ai • Turn ideas into AI, Lightning fast. Creators of PyTorch Lightning, Lightning AI Studio, TorchMetrics, Fabric, Lit-GPT, Lit-LLaMA. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
82%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
29 repos
Visible snapshot
15 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (25), Jupyter Notebook (1), TypeScript (1)
Average size
2.1K
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2026-08-14(12d ago)GitHub API fallback29 repositories
82%
of the visible star count comes from this organization's top three repositories.
2.1K
stars per repository in this same snapshot.
Python
is the most common language here, with 15 repositories updated in the last 90 days.
Why this rank
This organization stands out because one flagship repo drives 50% of its visible star count.
Flagship share 50%Breakout repo: pytorch-lightning
Organization pages work best when you separate portfolio breadth from flagship concentration. In ⚡️ Lightning AI 's case, the visible top three repositories account for about 82% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Python (25), Jupyter Notebook (1), TypeScript (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | lightning-ai/pytorch-lightning Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes. | Python | 31.3K |
| 2 | lightning-ai/litgpt 20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale. | Python | 13.6K |
| 3 | lightning-ai/lit-llama Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. | Python | 6.1K |
| 4 | lightning-ai/LitServe A minimal Python framework for building custom AI inference servers with full control over logic, batching, and scaling. | Python | 3.9K |
| 5 | lightning-ai/torchmetrics Machine learning metrics for distributed, scalable PyTorch applications. | Python | 2.5K |
| 6 | lightning-ai/lightning-thunder PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own. | Python | 1.5K |
| 7 | lightning-ai/deep-learning-project-template Pytorch Lightning code guideline for conferences | Python | 1.3K |
| 8 | lightning-ai/litData Speed up model training by fixing data loading. | Python | 611 |
| 9 | lightning-ai/dl-fundamentals Deep Learning Fundamentals -- Code material and exercises | Jupyter Notebook | 403 |
| 10 | lightning-ai/tutorials Collection of Pytorch lightning tutorial form as rich scripts automatically transformed to ipython notebooks. | Python | 318 |
| 11 | lightning-ai/engineering-class Lightning Bits: Engineering for Researchers repo | Python | 133 |
| 12 | lightning-ai/forked-pdb Python pdb for multiple processes | Python | 82 |
| 13 | lightning-ai/utilities Common Python utilities and GitHub Actions in Lightning Ecosystem | Python | 62 |
| 14 | lightning-ai/litAI LLM router + minimal agent framework in one. Call any LLM API with OpenAI format. Unified billing, tools, retries, fallback, logging. Build agents and AI apps in pure Python. Full control. Zero magic. | Python | 52 |
| 15 | lightning-ai/ecosystem-ci Automate issue discovery for your projects against Lightning nightly and releases. | Python | 46 |
| 16 | lightning-ai/LitModels Save, load, host, and share AI model checkpoints without slowing down training. Host on Lightning AI or your own cloud with enterprise-grade access controls. | Python | 40 |
| 17 | lightning-ai/LitLogger A minimal Python logger that tracks everything you try when building AI - metrics, prompts, models, etc, so you can see what changed and why. | Python | 37 |
| 18 | lightning-ai/lightning-Habana Lightning support for Intel Habana accelerators. | Python | 25 |
| 19 | lightning-ai/Lightning-multinode-templates Multinode templates for Pytorch Lightning | Python | 9 |
| 20 | lightning-ai/lightning-Graphcore | Python | 9 |
| 21 | lightning-ai/probot | TypeScript | 9 |
| 22 | lightning-ai/sdk SDK and CLI for lightning.ai platform. Develop and train AI with ease. | Python | 8 |
| 23 | lightning-ai/skills | Python | 6 |
| 24 | lightning-ai/litperf Lightweight performance tracker for Python code - zero overhead when disabled. | Python | 5 |
| 25 | lightning-ai/hello-studio Starter projects for Lightning Studios | Python | 5 |
| 26 | lightning-ai/lm-evaluation-harness A framework for few-shot evaluation of autoregressive language models. | Python | 3 |
| 27 | lightning-ai/litracer A tool for converting Lightning AI's LitData logs to Chrome-compatible trace files. | Go | 2 |
| 28 | lightning-ai/langchain-lightning Lightning AI sandbox adapter for langchain | Python | 0 |
| 29 | lightning-ai/skypilot Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, Slurm, 20+ clouds, on-prem). | 0 |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.