--- title: "huozi vs LLMs-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hit-scir-huozi-vs-rasbt-llms-from-scratch" tools: ["hit-scir-huozi", "rasbt-llms-from-scratch"] --- # huozi vs LLMs-from-scratch *GraphCanon updated Aug 24, 2026* ## Verdict Pick huozi if huozi is a Python-based large model framework with Apache-2.0 license for fine-tuning and NLP applications; pick LLMs-from-scratch if lLMs-from-scratch is a project-oriented repository aimed at building PyTorch-based language models from the ground up, with detailed step-by-step instructions. [huozi](https://github.com/HIT-SCIR/huozi) reports 393 GitHub stars, 26 forks, and 0 open issues, last pushed Sep 12, 2024. [LLMs-from-scratch](https://amzn.to/4fqvn0D) has 103k stars, 16k forks, and 2 open issues, last pushed Aug 10, 2026. Figures are from public GitHub metadata via [huozi's repository](https://github.com/HIT-SCIR/huozi) and [LLMs-from-scratch's repository](https://github.com/rasbt/LLMs-from-scratch). | | [huozi](/tools/hit-scir-huozi.md) | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | | --- | --- | --- | | Tagline | General-purpose large model for fine-tuning and applications | Implement a ChatGPT-like LLM in PyTorch from scratch, step by step | | Stars | 393 | 102,733 | | Forks | 26 | 15,748 | | Open issues | 0 | 2 | | Language | Python | Jupyter Notebook | | Adopt for | Huozi is a Python-based large model framework with Apache-2.0 license for fine-tuning and NLP applications. | LLMs-from-scratch is a project-oriented repository aimed at building PyTorch-based language models from the ground up, with detailed step-by-step instructions. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [huozi](/tools/hit-scir-huozi.md) | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 711d | 5d | | Open issues (now) | 0 | 2 | | Stars delta | -2 (30d) | +3.5k (30d) | | Open issues delta | 0 (30d) | -1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/hit-scir-huozi/trust.md) | [trust report](/tools/rasbt-llms-from-scratch/trust.md) | ## Decision facts: huozi - **Adopt for:** Huozi is a Python-based large model framework with Apache-2.0 license for fine-tuning and NLP applications. ## Decision facts: LLMs-from-scratch - **Adopt for:** LLMs-from-scratch is a project-oriented repository aimed at building PyTorch-based language models from the ground up, with detailed step-by-step instructions. ## Choose when ### Choose huozi if… - huozi is primarily Python; LLMs-from-scratch is Jupyter Notebook. - License: huozi is Apache-2.0, LLMs-from-scratch is Other. - Tags unique to huozi: fine-tuning, large language models, llm, nlp. - When working on projects that require fast integration of pre-trained language models through its streamlined fine-tuning capabilities. ### Choose LLMs-from-scratch if… - LLMs-from-scratch is primarily Jupyter Notebook; huozi is Python. - License: LLMs-from-scratch is Other, huozi is Apache-2.0. - Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, deep-learning. - - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework. ## When NOT to use huozi - If your project requires proprietary licensing, as Huozi is under the Apache-2.0 license which may not meet all business models' requirements. - When needing a framework with comprehensive support for visual data or other non-textual machine learning applications. ## When NOT to use LLMs-from-scratch - - If you are looking for a rapid deployment of an LLM without understanding its intricate structure - this tool requires extensive manual and conceptual work. - - You prefer frameworks with automatic model generation or other high-level abstractions that simplify the process. This repository emphasizes manual creation, which is more time-consuming but offers - a deeper learning experience. ## Common questions ### What is the difference between huozi and LLMs-from-scratch? huozi: General-purpose large model for fine-tuning and applications. LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step. See the comparison table for live GitHub stats and shared categories. ### When should I choose huozi over LLMs-from-scratch? Choose huozi over LLMs-from-scratch when huozi is primarily Python; LLMs-from-scratch is Jupyter Notebook; License: huozi is Apache-2.0, LLMs-from-scratch is Other; Tags unique to huozi: fine-tuning, large language models, llm, nlp; When working on projects that require fast integration of pre-trained language models through its streamlined fine-tuning capabilities. ### When should I choose LLMs-from-scratch over huozi? Choose LLMs-from-scratch over huozi when LLMs-from-scratch is primarily Jupyter Notebook; huozi is Python; License: LLMs-from-scratch is Other, huozi is Apache-2.0; Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, deep-learning; - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework. ### When should I avoid huozi? If your project requires proprietary licensing, as Huozi is under the Apache-2.0 license which may not meet all business models' requirements. When needing a framework with comprehensive support for visual data or other non-textual machine learning applications. ### When should I avoid LLMs-from-scratch? - If you are looking for a rapid deployment of an LLM without understanding its intricate structure - this tool requires extensive manual and conceptual work. - You prefer frameworks with automatic model generation or other high-level abstractions that simplify the process. This repository emphasizes manual creation, which is more time-consuming but offers a deeper learning experience. ### Is huozi or LLMs-from-scratch more popular on GitHub? LLMs-from-scratch has more GitHub stars (102,733 vs 393). Stars measure visibility, not whether either tool fits your constraints. ### Are huozi and LLMs-from-scratch open source? Yes - both are open-source projects on GitHub (huozi: Apache-2.0, LLMs-from-scratch: Other). ### Where can I find alternatives to huozi or LLMs-from-scratch? GraphCanon lists graph-backed alternatives at [huozi alternatives](/tools/hit-scir-huozi/alternatives) and [LLMs-from-scratch alternatives](/tools/rasbt-llms-from-scratch/alternatives) ([huozi markdown twin](/tools/hit-scir-huozi/alternatives.md), [LLMs-from-scratch markdown twin](/tools/rasbt-llms-from-scratch/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/hit-scir-huozi-vs-rasbt-llms-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, huozi or LLMs-from-scratch? huozi: Dormant. LLMs-from-scratch: 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 huozi and LLMs-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [huozi trust report](/tools/hit-scir-huozi/trust); [LLMs-from-scratch trust report](/tools/rasbt-llms-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hit-scir-huozi`](/api/graphcanon/graph?tool=hit-scir-huozi) - 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/_