--- title: "ChuanhuChatGPT vs LLMs-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/gaizhenbiao-chuanhuchatgpt-vs-rasbt-llms-from-scratch" tools: ["gaizhenbiao-chuanhuchatgpt", "rasbt-llms-from-scratch"] --- # ChuanhuChatGPT vs LLMs-from-scratch *GraphCanon updated Jul 15, 2026* ## Verdict Pick ChuanhuChatGPT when chuanhuChatGPT is primarily Python; LLMs-from-scratch is Jupyter Notebook; pick LLMs-from-scratch when lLMs-from-scratch is primarily Jupyter Notebook; ChuanhuChatGPT is Python. [ChuanhuChatGPT](https://huggingface.co/spaces/JohnSmith9982/ChuanhuChatGPT) reports 15k GitHub stars, 2.2k forks, and 129 open issues, last pushed Apr 30, 2026. [LLMs-from-scratch](https://amzn.to/4fqvn0D) has 99k stars, 15k forks, and 4 open issues, last pushed Jun 2, 2026. Figures are from public GitHub metadata via [ChuanhuChatGPT's repository](https://github.com/GaiZhenbiao/ChuanhuChatGPT) and [LLMs-from-scratch's repository](https://github.com/rasbt/LLMs-from-scratch). | | [ChuanhuChatGPT](/tools/gaizhenbiao-chuanhuchatgpt.md) | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | | --- | --- | --- | | Tagline | GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI. | Implement a ChatGPT-like LLM in PyTorch from scratch, step by step | | Stars | 15,300 | 98,899 | | Forks | 2,218 | 15,183 | | Open issues | 129 | 4 | | Language | Python | Jupyter Notebook | | 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. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | Other | | Categories | AI Agents, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ChuanhuChatGPT](/tools/gaizhenbiao-chuanhuchatgpt.md) | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | | --- | --- | --- | | Days since push | 75d | 38d | | Open issues (now) | 129 | 4 | | Full report | [trust report](/tools/gaizhenbiao-chuanhuchatgpt/trust.md) | [trust report](/tools/rasbt-llms-from-scratch/trust.md) | ## 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 ChuanhuChatGPT if… - ChuanhuChatGPT is primarily Python; LLMs-from-scratch is Jupyter Notebook. - License: ChuanhuChatGPT is GPL-3.0, LLMs-from-scratch is Other. - Tags unique to ChuanhuChatGPT: chatbot, chatglm, chatgpt-api, claude. - Also covers AI Agents. - ChuanhuChatGPT ships Docker support for self-hosted deployment. ### Choose LLMs-from-scratch if… - LLMs-from-scratch is primarily Jupyter Notebook; ChuanhuChatGPT is Python. - License: LLMs-from-scratch is Other, ChuanhuChatGPT is GPL-3.0. - 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 ChuanhuChatGPT - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## 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 ChuanhuChatGPT and LLMs-from-scratch? ChuanhuChatGPT: GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.. 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 ChuanhuChatGPT over LLMs-from-scratch? Choose ChuanhuChatGPT over LLMs-from-scratch when ChuanhuChatGPT is primarily Python; LLMs-from-scratch is Jupyter Notebook; License: ChuanhuChatGPT is GPL-3.0, LLMs-from-scratch is Other; Tags unique to ChuanhuChatGPT: chatbot, chatglm, chatgpt-api, claude; Also covers AI Agents; ChuanhuChatGPT ships Docker support for self-hosted deployment. ### When should I choose LLMs-from-scratch over ChuanhuChatGPT? Choose LLMs-from-scratch over ChuanhuChatGPT when LLMs-from-scratch is primarily Jupyter Notebook; ChuanhuChatGPT is Python; License: LLMs-from-scratch is Other, ChuanhuChatGPT is GPL-3.0; 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 ChuanhuChatGPT? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### 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 ChuanhuChatGPT or LLMs-from-scratch more popular on GitHub? LLMs-from-scratch has more GitHub stars (98,899 vs 15,300). Stars measure visibility, not whether either tool fits your constraints. ### Are ChuanhuChatGPT and LLMs-from-scratch open source? Yes - both are open-source projects on GitHub (ChuanhuChatGPT: GPL-3.0, LLMs-from-scratch: Other). ### Where can I find alternatives to ChuanhuChatGPT or LLMs-from-scratch? GraphCanon lists graph-backed alternatives at [ChuanhuChatGPT alternatives](/tools/gaizhenbiao-chuanhuchatgpt/alternatives) and [LLMs-from-scratch alternatives](/tools/rasbt-llms-from-scratch/alternatives) ([ChuanhuChatGPT markdown twin](/tools/gaizhenbiao-chuanhuchatgpt/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/gaizhenbiao-chuanhuchatgpt-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, ChuanhuChatGPT or LLMs-from-scratch? ChuanhuChatGPT: Steady. LLMs-from-scratch: Steady. 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 ChuanhuChatGPT and LLMs-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ChuanhuChatGPT trust report](/tools/gaizhenbiao-chuanhuchatgpt/trust); [LLMs-from-scratch trust report](/tools/rasbt-llms-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=gaizhenbiao-chuanhuchatgpt`](/api/graphcanon/graph?tool=gaizhenbiao-chuanhuchatgpt) - 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/_