⚡ LitGPT

20+ high-performance LLMs with recipes to pretrain, finetune, and deploy at scale.

✅ From scratch implementations      ✅ No abstractions         ✅ Beginner friendly
   ✅ Flash attention                   ✅ FSDP                    ✅ LoRA, QLoRA, Adapter
✅ Reduce GPU memory (fp4/8/16/32)   ✅ 1-1000+ GPUs/TPUs       ✅ 20+ LLMs         

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Quick start • Models • Finetune • Deploy • All workflows • Features • Recipes (YAML) • Lightning AI • Tutorials

 

 

Looking for GPUs?

Over 340,000 developers use Lightning Cloud - purpose-built for PyTorch and PyTorch Lightning. - GPUs from $0.19.
- Clusters: frontier-grade training/inference clusters.
- AI Studio (vibe train): workspaces where AI helps you debug, tune and vibe train. - AI Studio (vibe deploy): workspaces where AI helps you optimize, and deploy models.
- Notebooks: Persistent GPU workspaces where AI helps you code and analyze. - Inference: Deploy models as inference APIs.

Finetune, pretrain, and inference LLMs Lightning fast ⚡⚡

Every LLM is implemented from scratch with no abstractions and full control, making them blazing fast, minimal, and performant at enterprise scale.

✅ Enterprise ready - Apache 2.0 for unlimited enterprise use.

✅ Developer friendly - Easy debugging with no abstraction layers and single file implementations.

✅ Optimized performance - Models designed to maximize performance, reduce costs, and speed up training.

✅ Proven recipes - Highly-optimized training/finetuning recipes tested at enterprise scale.

 

Quick start

Install LitGPT

pip install 'litgpt[extra]'

Load and use any of the 20+ LLMs:

from litgpt import LLM

llm = LLM.load("microsoft/phi-2")
text = llm.generate("Fix the spelling: Every fall, the family goes to the mountains.")
print(text)
# Corrected Sentence: Every fall, the family goes to the mountains.

 

✅ Optimized for fast inference

✅ Quantization

✅ Runs on low-memory GPUs

✅ No layers of internal abstractions

✅ Optimized for production scale

Advanced install options

Install from source:

git clone https://github.com/Lightning-AI/litgpt
cd litgpt
# if using uv
uv sync --all-extras
# if using pip
pip install -e ".[extra,compiler,test]"

Explore the full Python API docs.

 

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Choose from 20+ LLMs

Every model is written from scratch to maximize performance and remove layers of abstraction:

Model	Model size	Author	Reference
Llama 3, 3.1, 3.2, 3.3	1B, 3B, 8B, 70B, 405B	Meta AI	Meta AI 2024
Code Llama	7B, 13B, 34B, 70B	Meta AI	Rozière et al. 2023
CodeGemma	7B	Google	Google Team, Google Deepmind
Gemma 2	2B, 9B, 27B	Google	Google Team, Google Deepmind
Phi 4	14B	Microsoft Research	Abdin et al. 2024
Qwen2.5	0.5B, 1.5B, 3B, 7B, 14B, 32B, 72B	Alibaba Group	Qwen Team 2024
Qwen2.5 Coder	0.5B, 1.5B, 3B, 7B, 14B, 32B	Alibaba Group	Hui, Binyuan et al. 2024
R1 Distill Llama	8B, 70B	DeepSeek AI	DeepSeek AI 2025
...	...	...	...

See full list of 20+ LLMs

 

All models

Model	Model size	Author	Reference
CodeGemma	7B	Google	Google Team, Google Deepmind
Code Llama	7B, 13B, 34B, 70B	Meta AI	Rozière et al. 2023
Falcon	7B, 40B, 180B	TII UAE	TII 2023
Falcon 3	1B, 3B, 7B, 10B	TII UAE	TII 2024
FreeWilly2 (Stable Beluga 2)	70B	Stability AI	Stability AI 2023
Function Calling Llama 2	7B	Trelis	Trelis et al. 2023
Gemma	2B, 7B	Google	Google Team, Google Deepmind
Gemma 2	9B, 27B	Google	Google Team, Google Deepmind
Gemma 3	1B, 4B, 12B, 27B	Google	Google Team, Google Deepmind
Llama 2	7B, 13B, 70B	Meta AI	Touvron et al. 2023
Llama 3.1	8B, 70B	Meta AI	Meta AI 2024
Llama 3.2	1B, 3B	Meta AI	Meta AI 2024
Llama 3.3	70B	Meta AI	Meta AI 2024
Mathstral	7B	Mistral AI	Mistral AI 2024
MicroLlama	300M	Ken Wang	MicroLlama repo
Mixtral MoE	8x7B	Mistral AI	Mistral AI 2023
Mistral	7B, 123B	Mistral AI	Mistral AI 2023
Mixtral MoE	8x22B	Mistral AI	Mistral AI 2024
OLMo	1B, 7B	Allen Institute for AI (AI2)	Groeneveld et al. 2024
OpenLLaMA	3B, 7B, 13B	OpenLM Research	Geng & Liu 2023
Phi 1.5 & 2	1.3B, 2.7B	Microsoft Research	Li et al. 2023
Phi 3	3.8B	Microsoft Research	Abdin et al. 2024
Phi 4	14B	Microsoft Research	Abdin et al. 2024
Phi 4 Mini Instruct	3.8B	Microsoft Research	Microsoft 2025
Phi 4 Mini Reasoning	3.8B	Microsoft Research	Xu, Peng et al. 2025
Phi 4 Reasoning	3.8B	Microsoft Research	Abdin et al. 2025
Phi 4 Reasoning Plus	3.8B	Microsoft Research	Abdin et al. 2025
Platypus	7B, 13B, 70B	Lee et al.	Lee, Hunter, and Ruiz 2023
Pythia	{14,31,70,160,410}M, {1,1.4,2.8,6.9,12}B	EleutherAI	Biderman et al. 2023
Qwen2.5	0.5B, 1.5B, 3B, 7B, 14B, 32B, 72B	Alibaba Group	Qwen Team 2024
Qwen2.5 Coder	0.5B, 1.5B, 3B, 7B, 14B, 32B	Alibaba Group	Hui, Binyuan et al. 2024
Qwen2.5 1M (Long Context)	7B, 14B	Alibaba Group	Qwen Team 2025
Qwen2.5 Math	1.5B, 7B, 72B	Alibaba Group	An, Yang et al. 2024
QwQ	32B	Alibaba Group	Qwen Team 2025
QwQ-Preview	32B	Alibaba Group	Qwen Team 2024
Qwen3	0.6B, 1.7B, 4B{Hybrid, Thinking-2507, Instruct-2507}, 8B, 14B, 32B	Alibaba Group	Qwen Team 2025
Qwen3 MoE	30B{Hybrid, Thinking-2507, Instruct-2507}, 235B{Hybrid, Thinking-2507, Instruct-2507}	Alibaba Group	Qwen Team 2025
R1 Distill Llama	8B, 70B	DeepSeek AI	DeepSeek AI 2025
SmolLM2	135M, 360M, 1.7B	Hugging Face	Hugging Face 2024
Salamandra	2B, 7B	Barcelona Supercomputing Centre	BSC-LTC 2024
StableCode	3B	Stability AI	Stability AI 2023
StableLM	3B, 7B	Stability AI	Stability AI 2023
StableLM Zephyr	3B	Stability AI	Stability AI 2023
TinyLlama	1.1B	Zhang et al.	Zhang et al. 2023

Tip: You can list all available models by running the litgpt download list command.

 

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Workflows

Finetune • Pretrain • Continued pretraining • Evaluate • Deploy • Test

 

Use the command line interface to run advanced workflows such as pretraining or finetuning on your own data.

All workflows

After installing LitGPT, select the model and workflow to run (finetune, pretrain, evaluat