--- title: "FlagAI vs LLMs-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/flagai-open-flagai-vs-rasbt-llms-from-scratch" tools: ["flagai-open-flagai", "rasbt-llms-from-scratch"] --- # FlagAI vs LLMs-from-scratch *GraphCanon updated Aug 16, 2026* ## Verdict Pick FlagAI if flagAI is identified by its fast and scalable toolkit designed for managing large-scale AI models in Python, under an Apache-2.0 license; 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. [FlagAI](https://github.com/FlagAI-Open/FlagAI) reports 3.9k GitHub stars, 416 forks, and 22 open issues, last pushed Jul 13, 2026. [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 [FlagAI's repository](https://github.com/FlagAI-Open/FlagAI) and [LLMs-from-scratch's repository](https://github.com/rasbt/LLMs-from-scratch). | | [FlagAI](/tools/flagai-open-flagai.md) | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | | --- | --- | --- | | Tagline | Fast, easy-to-use framework for large-scale AI models. | Implement a ChatGPT-like LLM in PyTorch from scratch, step by step | | Stars | 3,870 | 102,733 | | Forks | 416 | 15,748 | | Open issues | 22 | 2 | | Language | Python | Jupyter Notebook | | Adopt for | FlagAI is identified by its fast and scalable toolkit designed for managing large-scale AI models in Python, under an Apache-2.0 license. | 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._ | | [FlagAI](/tools/flagai-open-flagai.md) | [LLMs-from-scratch](/tools/rasbt-llms-from-scratch.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 33d | 5d | | Open issues (now) | 22 | 2 | | Stars delta | +2 (30d) | +3.5k (30d) | | Open issues delta | 0 (30d) | -1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/flagai-open-flagai/trust.md) | [trust report](/tools/rasbt-llms-from-scratch/trust.md) | ## Decision facts: FlagAI - **Adopt for:** FlagAI is identified by its fast and scalable toolkit designed for managing large-scale AI models in Python, under an Apache-2.0 license. ## 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 FlagAI if… - FlagAI is primarily Python; LLMs-from-scratch is Jupyter Notebook. - License: FlagAI is Apache-2.0, LLMs-from-scratch is Other. - Tags unique to FlagAI: extensible, fast, large-scale models. - FlagAI ships Docker support for self-hosted deployment. - When you prioritize speed and extensibility during the development of large-scale AI models with a focus on easy-to-use interfaces. ### Choose LLMs-from-scratch if… - LLMs-from-scratch is primarily Jupyter Notebook; FlagAI is Python. - License: LLMs-from-scratch is Other, FlagAI 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 FlagAI - If your project necessitates a deep level of customization that might not be supported by FlagAI's framework. - If you are working with smaller datasets, the overhead provided by FlagAI’s scalability features could be unnecessary and potentially inefficient. ## 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 FlagAI and LLMs-from-scratch? FlagAI: Fast, easy-to-use framework for large-scale AI models.. 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 FlagAI over LLMs-from-scratch? Choose FlagAI over LLMs-from-scratch when FlagAI is primarily Python; LLMs-from-scratch is Jupyter Notebook; License: FlagAI is Apache-2.0, LLMs-from-scratch is Other; Tags unique to FlagAI: extensible, fast, large-scale models; FlagAI ships Docker support for self-hosted deployment; When you prioritize speed and extensibility during the development of large-scale AI models with a focus on easy-to-use interfaces. ### When should I choose LLMs-from-scratch over FlagAI? Choose LLMs-from-scratch over FlagAI when LLMs-from-scratch is primarily Jupyter Notebook; FlagAI is Python; License: LLMs-from-scratch is Other, FlagAI 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 FlagAI? If your project necessitates a deep level of customization that might not be supported by FlagAI's framework. If you are working with smaller datasets, the overhead provided by FlagAI’s scalability features could be unnecessary and potentially inefficient. ### 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 FlagAI or LLMs-from-scratch more popular on GitHub? LLMs-from-scratch has more GitHub stars (102,733 vs 3,870). Stars measure visibility, not whether either tool fits your constraints. ### Are FlagAI and LLMs-from-scratch open source? Yes - both are open-source projects on GitHub (FlagAI: Apache-2.0, LLMs-from-scratch: Other). ### Where can I find alternatives to FlagAI or LLMs-from-scratch? GraphCanon lists graph-backed alternatives at [FlagAI alternatives](/tools/flagai-open-flagai/alternatives) and [LLMs-from-scratch alternatives](/tools/rasbt-llms-from-scratch/alternatives) ([FlagAI markdown twin](/tools/flagai-open-flagai/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/flagai-open-flagai-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, FlagAI or LLMs-from-scratch? FlagAI: Steady. 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 FlagAI and LLMs-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FlagAI trust report](/tools/flagai-open-flagai/trust); [LLMs-from-scratch trust report](/tools/rasbt-llms-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=flagai-open-flagai`](/api/graphcanon/graph?tool=flagai-open-flagai) - 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/_