LlamaFactory vs litgpt
LLM training and fine-tuning toolkits compared
LlamaFactory and litgpt are Python toolkits for adapting large language models, with workflows for fine-tuning and memory-conscious training. LlamaFactory also covers vision and other modalities and offers a web interface, while litgpt emphasizes configurable LLM workflows, readable implementations, evaluation, and serving.
LlamaFactory: Fine-Tune Large Language and Vision Models
LlamaFactory provides CLI and web interfaces for fine-tuning a broad range of language and vision models. It supports parameter-efficient methods and preference training, with workflows for training, inference, and model export.
litgpt: Train, Fine-Tune, and Serve Large Language Models
LitGPT is a Python toolkit for pretraining, fine-tuning, evaluating, and serving a range of large language models. It offers configurable workflows and efficient training options for researchers and teams that want direct control over model code.
| LlamaFactory | litgpt | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Stars | 75.3k | 13.7k |
| Forks | 9.2k | 1.5k |
| Last analyzed | Oct 3, 2026 | Oct 11, 2026 |
Key differences
- LlamaFactory supports language and vision models, with some workflows for video and audio; litgpt focuses on large language models.
- LlamaFactory includes supervised fine-tuning, reward modeling, and preference or reinforcement-learning methods such as DPO and PPO; litgpt includes pretraining, continued pretraining, evaluation, and serving workflows.
- LlamaFactory offers a Gradio web interface alongside CLI commands; litgpt provides CLI and Python API access, with YAML recipes and command-line overrides.
- Both support LoRA and QLoRA; litgpt additionally describes multi-GPU training through fully sharded data parallelism, optional CPU offloading, and TPU support.
- Both use Python and have Apache-2.0 licenses. The supplied figures list 75.3k stars and 9.2k forks for LlamaFactory, and 13.7k stars and 1.5k forks for litgpt.
Choose LlamaFactory if you…
- need a web interface as well as CLI workflows for model adaptation.
- want training options that include reward modeling or preference methods such as DPO and PPO.
- are adapting supported vision, video, or audio models as well as language models.
Choose litgpt if you…
- want workflows that cover pretraining, evaluation, and serving in addition to fine-tuning.
- prefer configurable YAML recipes and implementations you can inspect or modify.
- need to explore multi-GPU training, CPU offloading, or TPU support.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.