--- title: "FineTuningLLMs vs litgpt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dvgodoy-finetuningllms-vs-lightning-ai-litgpt" tools: ["dvgodoy-finetuningllms", "lightning-ai-litgpt"] --- # FineTuningLLMs vs litgpt *GraphCanon updated Sep 20, 2026* ## Verdict Pick FineTuningLLMs if fineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks; pick litgpt if litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license. [FineTuningLLMs](https://github.com/dvgodoy/FineTuningLLMs) reports 865 GitHub stars, 119 forks, and 4 open issues, last pushed Feb 28, 2026. [litgpt](https://lightning.ai) has 14k stars, 1.5k forks, and 290 open issues, last pushed Sep 14, 2026. Figures are from public GitHub metadata via [FineTuningLLMs's repository](https://github.com/dvgodoy/FineTuningLLMs) and [litgpt's repository](https://github.com/Lightning-AI/litgpt). | | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [litgpt](/tools/lightning-ai-litgpt.md) | | --- | --- | --- | | Tagline | Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face' | High-performance LLMs for pretraining, finetuning, and deployment | | Stars | 865 | 13,667 | | Forks | 119 | 1,503 | | Open issues | 4 | 290 | | Language | Jupyter Notebook | Python | | Adopt for | FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. | litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | LLM Frameworks, Model Training | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FineTuningLLMs](/tools/dvgodoy-finetuningllms.md) | [litgpt](/tools/lightning-ai-litgpt.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 203d | 3d | | Open issues (now) | 4 | 290 | | Stars delta | +14 (30d) | +62 (30d) | | Open issues delta | 0 (30d) | +18 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/dvgodoy-finetuningllms/trust.md) | [trust report](/tools/lightning-ai-litgpt/trust.md) | ## Decision facts: FineTuningLLMs - **Adopt for:** FineTuningLLMs is designed for users familiar with PyTorch and Hugging Face who seek practical guidance via Jupyter Notebooks. ## Decision facts: litgpt - **Adopt for:** litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license. ## Choose when ### Choose FineTuningLLMs if… - FineTuningLLMs is primarily Jupyter Notebook; litgpt is Python. - License: FineTuningLLMs is MIT, litgpt is Apache-2.0. - Tags unique to FineTuningLLMs: bitsandbytes, fine-tuning, finetuning, hugging-face. - You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem ### Choose litgpt if… - litgpt is primarily Python; FineTuningLLMs is Jupyter Notebook. - License: litgpt is Apache-2.0, FineTuningLLMs is MIT. - Tags unique to litgpt: ai, artificial-intelligence, deep-learning, llm. - Also covers Inference & Serving. - When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment. ## When NOT to use FineTuningLLMs - Not interested in PyTorch; prefer TensorFlow or another framework - Seek theoretical background over practical applications ## When NOT to use litgpt - If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based. - When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases. - If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license. ## Common questions ### What is the difference between FineTuningLLMs and litgpt? FineTuningLLMs: Official repository for 'A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face'. litgpt: High-performance LLMs for pretraining, finetuning, and deployment. See the comparison table for live GitHub stats and shared categories. ### When should I choose FineTuningLLMs over litgpt? Choose FineTuningLLMs over litgpt when FineTuningLLMs is primarily Jupyter Notebook; litgpt is Python; License: FineTuningLLMs is MIT, litgpt is Apache-2.0; Tags unique to FineTuningLLMs: bitsandbytes, fine-tuning, finetuning, hugging-face; You need hands-on, step-by-step instructions using PyTorch and the Hugging Face ecosystem. ### When should I choose litgpt over FineTuningLLMs? Choose litgpt over FineTuningLLMs when litgpt is primarily Python; FineTuningLLMs is Jupyter Notebook; License: litgpt is Apache-2.0, FineTuningLLMs is MIT; Tags unique to litgpt: ai, artificial-intelligence, deep-learning, llm; Also covers Inference & Serving; When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment. ### When should I avoid FineTuningLLMs? Not interested in PyTorch; prefer TensorFlow or another framework Seek theoretical background over practical applications ### When should I avoid litgpt? If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based. When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases. If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license. ### Is FineTuningLLMs or litgpt more popular on GitHub? litgpt has more GitHub stars (13,667 vs 865). Stars measure visibility, not whether either tool fits your constraints. ### Are FineTuningLLMs and litgpt open source? Yes - both are open-source projects on GitHub (FineTuningLLMs: MIT, litgpt: Apache-2.0). ### Where can I find alternatives to FineTuningLLMs or litgpt? GraphCanon lists graph-backed alternatives at [FineTuningLLMs alternatives](/tools/dvgodoy-finetuningllms/alternatives) and [litgpt alternatives](/tools/lightning-ai-litgpt/alternatives) ([FineTuningLLMs markdown twin](/tools/dvgodoy-finetuningllms/alternatives.md), [litgpt markdown twin](/tools/lightning-ai-litgpt/alternatives.md)), 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](/compare/dvgodoy-finetuningllms-vs-lightning-ai-litgpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FineTuningLLMs or litgpt? FineTuningLLMs: Slowing. litgpt: 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 FineTuningLLMs and litgpt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FineTuningLLMs trust report](/tools/dvgodoy-finetuningllms/trust); [litgpt trust report](/tools/lightning-ai-litgpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dvgodoy-finetuningllms`](/api/graphcanon/graph?tool=dvgodoy-finetuningllms) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_