--- title: "LLMs-from-scratch vs Chain-of-ThoughtsPapers" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/rasbt-llms-from-scratch-vs-timothyxxx-chain-of-thoughtspapers" tools: ["rasbt-llms-from-scratch", "timothyxxx-chain-of-thoughtspapers"] --- # LLMs-from-scratch vs Chain-of-ThoughtsPapers *GraphCanon updated Jul 11, 2026* ## Verdict 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; pick Chain-of-ThoughtsPapers if chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. [LLMs-from-scratch](https://amzn.to/4fqvn0D) reports 99k GitHub stars, 15k forks, and 4 open issues, last pushed Jun 2, 2026. [Chain-of-ThoughtsPapers](https://github.com/Timothyxxx/Chain-of-ThoughtsPapers) has 2.1k stars, 142 forks, and 0 open issues, last pushed Oct 5, 2023. Figures are from public GitHub metadata via [LLMs-from-scratch's repository](https://github.com/rasbt/LLMs-from-scratch) and [Chain-of-ThoughtsPapers's repository](https://github.com/Timothyxxx/Chain-of-ThoughtsPapers). | | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | [Chain-of-ThoughtsPapers](/tools/timothyxxx-chain-of-thoughtspapers.md) | | --- | --- | --- | | Tagline | Implement a ChatGPT-like LLM in PyTorch from scratch, step by step | A curated list of papers exploring chain-of-thought reasoning in large language models. | | Stars | 98,899 | 2,106 | | Forks | 15,183 | 142 | | Open issues | 4 | 0 | | Language | 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. | Chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. | | Persona | - | end user agent | | Runtime | - | - | | License | Other | - | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | [Chain-of-ThoughtsPapers](/tools/timothyxxx-chain-of-thoughtspapers.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Archived (8%) | | Days since push | 38d | 1010d | | Archived on GitHub | No | Yes | | Open issues (now) | 4 | 0 | | Full report | [trust report](/tools/rasbt-llms-from-scratch/trust.md) | [trust report](/tools/timothyxxx-chain-of-thoughtspapers/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. ## Decision facts: Chain-of-ThoughtsPapers - **Adopt for:** Chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. - **Persona:** end user agent ## Choose when ### Choose LLMs-from-scratch if… - Tags unique to LLMs-from-scratch: deep-learning, ai, artificial-intelligence, attention-mechanism. - - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework. - More GitHub stars (99k vs 2.1k) - visibility, not fit. ### Choose Chain-of-ThoughtsPapers if… - Tags unique to Chain-of-ThoughtsPapers: gpt-3, chain-of-thought, large-language-models, prompt-learning. - When you need insights into foundational and cutting-edge research on how language models can be prompted or structured to reason logically. - Leaner open-issue backlog (0). ## 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丰 - a deeper learning experience. ## When NOT to use Chain-of-ThoughtsPapers - If your focus is on unrelated areas such as image processing or speech recognition, where chain-of-thought reasoning in LLMs does not directly play a role. - For projects requiring immediate practical coding implementations — this repository primarily focuses on research and theoretical underpinnings rather than ready-to-use software libraries or codebases - In scenarios necessitating alternative approaches to language model training which do not emphasize step-by-step reasoning, such as models trained purely for pattern recognition without emphasis on a - what_is_missing ## Common questions ### What is the difference between LLMs-from-scratch and Chain-of-ThoughtsPapers? LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step. Chain-of-ThoughtsPapers: A curated list of papers exploring chain-of-thought reasoning in large language models.. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLMs-from-scratch over Chain-of-ThoughtsPapers? Choose LLMs-from-scratch over Chain-of-ThoughtsPapers when Tags unique to LLMs-from-scratch: deep-learning, ai, artificial-intelligence, attention-mechanism; - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework; More GitHub stars (99k vs 2.1k) - visibility, not fit. ### When should I choose Chain-of-ThoughtsPapers over LLMs-from-scratch? Choose Chain-of-ThoughtsPapers over LLMs-from-scratch when Tags unique to Chain-of-ThoughtsPapers: gpt-3, chain-of-thought, large-language-models, prompt-learning; When you need insights into foundational and cutting-edge research on how language models can be prompted or structured to reason logically; Leaner open-issue backlog (0). ### 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丰 a deeper learning experience. ### When should I avoid Chain-of-ThoughtsPapers? If your focus is on unrelated areas such as image processing or speech recognition, where chain-of-thought reasoning in LLMs does not directly play a role. For projects requiring immediate practical coding implementations — this repository primarily focuses on research and theoretical underpinnings rather than ready-to-use software libraries or codebases In scenarios necessitating alternative approaches to language model training which do not emphasize step-by-step reasoning, such as models trained purely for pattern recognition without emphasis on a what_is_missing ### Is LLMs-from-scratch or Chain-of-ThoughtsPapers more popular on GitHub? LLMs-from-scratch has more GitHub stars (98,899 vs 2,106). Stars measure visibility, not whether either tool fits your constraints. ### Are LLMs-from-scratch and Chain-of-ThoughtsPapers open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to LLMs-from-scratch or Chain-of-ThoughtsPapers? GraphCanon lists graph-backed alternatives at [LLMs-from-scratch alternatives](/tools/rasbt-llms-from-scratch/alternatives) and [Chain-of-ThoughtsPapers alternatives](/tools/timothyxxx-chain-of-thoughtspapers/alternatives) ([LLMs-from-scratch markdown twin](/tools/rasbt-llms-from-scratch/alternatives.md), [Chain-of-ThoughtsPapers markdown twin](/tools/timothyxxx-chain-of-thoughtspapers/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/rasbt-llms-from-scratch-vs-timothyxxx-chain-of-thoughtspapers.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLMs-from-scratch or Chain-of-ThoughtsPapers? LLMs-from-scratch: Steady. Chain-of-ThoughtsPapers: Archived. 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 LLMs-from-scratch and Chain-of-ThoughtsPapers? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLMs-from-scratch trust report](/tools/rasbt-llms-from-scratch/trust); [Chain-of-ThoughtsPapers trust report](/tools/timothyxxx-chain-of-thoughtspapers/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=rasbt-llms-from-scratch`](/api/graphcanon/graph?tool=rasbt-llms-from-scratch) - 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/_