Home/Compare/LLMs-from-scratch vs awesome-llm-apps

Comparison

LLMs-from-scratch vs awesome-llm-apps

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 awesome-llm-apps if awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python.

Markdown twin · LLMs-from-scratch alternatives · awesome-llm-apps alternatives

GraphCanon updated 3d

LLMs-from-scratch logo

LLMs-from-scratch

rasbt/LLMs-from-scratch

103kpushed Aug 10, 2026
vs
awesome-llm-apps logo

awesome-llm-apps

Shubhamsaboo/awesome-llm-apps

131kpushed Aug 3, 2026

Trust & integrity

SignalLLMs-from-scratchawesome-llm-apps
Maintenance
Very active (5d since push)
As of 3d · github_public_v1
Very active (4d since push)
As of 1w · github_public_v1
Provenance
Not a fork · Personal account
As of 3d · github_public_v1
Not a fork · Personal account
As of 1w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
awesome-llm-apps
Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.

Stars

LLMs-from-scratch
103k
awesome-llm-apps
131k

Forks

LLMs-from-scratch
16k
awesome-llm-apps
19k

Open issues

LLMs-from-scratch
2
awesome-llm-apps
13

Language

LLMs-from-scratch
Jupyter Notebook
awesome-llm-apps
Python

Adopt for

LLMs-from-scratch
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.
awesome-llm-apps
awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python.

Persona

LLMs-from-scratch
-
awesome-llm-apps
-

Runtime

LLMs-from-scratch
-
awesome-llm-apps
-

License

LLMs-from-scratch
Other
awesome-llm-apps
The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license.

Last pushed

LLMs-from-scratch
Aug 10, 2026
awesome-llm-apps
Aug 3, 2026

Categories

LLMs-from-scratch
LLM Frameworks, Model Training
awesome-llm-apps
AI Agents, Data & Retrieval

Trust and health

Days since push

LLMs-from-scratch
5d
awesome-llm-apps
4d

Open issues (now)

LLMs-from-scratch
2
awesome-llm-apps
13

Stars delta

LLMs-from-scratch
+3.5k (30d)
awesome-llm-apps
+14k (30d)

Open issues delta

LLMs-from-scratch
-1 (30d)
awesome-llm-apps
+6 (30d)

Full report

LLMs-from-scratch
Trust report
awesome-llm-apps
Trust report

Typed relationship

LLMs-from-scratch alternative awesome-llm-appsawesome-llm-apps

Choose LLMs-from-scratch if…

  • LLMs-from-scratch is primarily Jupyter Notebook; awesome-llm-apps is Python.
  • License: LLMs-from-scratch is Other, awesome-llm-apps is Apache-2.0.
  • awesome-llm-apps
  • Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, deep-learning.
  • Also covers LLM Frameworks, Model Training.
  • - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework.

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.

Choose awesome-llm-apps if…

  • awesome-llm-apps is primarily Python; LLMs-from-scratch is Jupyter Notebook.
  • License: awesome-llm-apps is Apache-2.0, LLMs-from-scratch is Other.
  • Pricing: Free with open-source licensing, but commercial exploitation is allowed..
  • awesome-llm-apps
  • Tags unique to awesome-llm-apps: agents, applications, customizable, deployable.
  • Also covers AI Agents, Data & Retrieval.
  • When you need quick implementations of various real-world use cases for AI Agents and RAG.

When NOT to use awesome-llm-apps

  • If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch.
  • When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: LLMs-from-scratch 103k · awesome-llm-apps 131k (synced Aug 16, 2026).

Common questions

What is the difference between LLMs-from-scratch and awesome-llm-apps?
LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step. awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. See the comparison table for live GitHub stats and shared categories.
When should I choose LLMs-from-scratch over awesome-llm-apps?
Choose LLMs-from-scratch over awesome-llm-apps when LLMs-from-scratch is primarily Jupyter Notebook; awesome-llm-apps is Python; License: LLMs-from-scratch is Other, awesome-llm-apps is Apache-2.0; awesome-llm-apps; Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, deep-learning; Also covers LLM Frameworks, Model Training; - You are an advanced practitioner aiming to fully understand the underpinnings of LLMs using PyTorch as your primary framework.
When should I choose awesome-llm-apps over LLMs-from-scratch?
Choose awesome-llm-apps over LLMs-from-scratch when awesome-llm-apps is primarily Python; LLMs-from-scratch is Jupyter Notebook; License: awesome-llm-apps is Apache-2.0, LLMs-from-scratch is Other; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; awesome-llm-apps; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; Also covers AI Agents, Data & Retrieval; When you need quick implementations of various real-world use cases for AI Agents and RAG.
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.
When should I avoid awesome-llm-apps?
If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.
Is LLMs-from-scratch or awesome-llm-apps more popular on GitHub?
awesome-llm-apps has more GitHub stars (131,230 vs 102,733). Stars measure visibility, not whether either tool fits your constraints.
Are LLMs-from-scratch and awesome-llm-apps open source?
Yes - both are open-source projects on GitHub (LLMs-from-scratch: Other, awesome-llm-apps: Apache-2.0).
Where can I find alternatives to LLMs-from-scratch or awesome-llm-apps?
GraphCanon lists graph-backed alternatives at LLMs-from-scratch alternatives and awesome-llm-apps alternatives (LLMs-from-scratch markdown twin, awesome-llm-apps markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, LLMs-from-scratch or awesome-llm-apps?
LLMs-from-scratch: Very active. awesome-llm-apps: 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 LLMs-from-scratch and awesome-llm-apps?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLMs-from-scratch trust report; awesome-llm-apps trust report.

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