Comparison
LLMs-from-scratch vs awesome-llm-apps
Verdict
Pick LLMs-from-scratch if lLMs-from-scratch is a guide for building a ChatGPT-like language model using PyTorch, aimed at educational purposes and designed for use with accessible hardware; 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 Sep 20, 2026
19views this month
vs
Trust & integrity
| Signal | LLMs-from-scratch | awesome-llm-apps |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Very active (4d since push) As of Sep 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 7, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- 105k
- awesome-llm-apps
- 136k
Forks
- LLMs-from-scratch
- 16k
- awesome-llm-apps
- 20k
Open issues
- LLMs-from-scratch
- 2
- awesome-llm-apps
- 10
Language
- LLMs-from-scratch
- Jupyter Notebook
- awesome-llm-apps
- Python
Adopt for
- LLMs-from-scratch
- LLMs-from-scratch is a guide for building a ChatGPT-like language model using PyTorch, aimed at educational purposes and designed for use with accessible hardware.
- 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
- The license is not specified as a standard open-source license, indicating that users should review the license terms carefully before use.
- 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
- Sep 17, 2026
- awesome-llm-apps
- Sep 2, 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
- 0d
- awesome-llm-apps
- 4d
Open issues (now)
- LLMs-from-scratch
- 2
- awesome-llm-apps
- 10
Stars delta
- LLMs-from-scratch
- +2.4k (30d)
- awesome-llm-apps
- +5.2k (30d)
Open issues delta
- LLMs-from-scratch
- 0 (30d)
- awesome-llm-apps
- -3 (30d)
OSV dependency advisories
- LLMs-from-scratch
- Published findings
- awesome-llm-apps
- No lockfile (source not queried)
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.
- Requirements: Min 8 GB RAM; The code automatically utilizes GPUs if they are available, but it is designed to run on conventional laptops without specialized hardware..
- awesome-llm-apps
- Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, deep-learning.
- Also covers LLM Frameworks, Model Training.
- When you are interested in understanding the inner workings of large language models and want to build one from scratch using PyTorch.
When NOT to use LLMs-from-scratch
- If you are looking for a quick and efficient way to deploy a pre-trained language model without delving into the implementation details.
- When you require a production-ready solution, as LLMs-from-scratch is primarily designed for educational purposes and may not be optimized for industrial use.
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 (rasbt/LLMs-from-scratch) · observed Sep 20, 2026
- GitHub forks (rasbt/LLMs-from-scratch) · observed Sep 20, 2026
- Last push (rasbt/LLMs-from-scratch) · observed Sep 17, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (Shubhamsaboo/awesome-llm-apps) · observed Sep 20, 2026
- GitHub forks (Shubhamsaboo/awesome-llm-apps) · observed Sep 20, 2026
- Last push (Shubhamsaboo/awesome-llm-apps) · observed Sep 2, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LLMs-from-scratch 105k · awesome-llm-apps 136k (synced Sep 20, 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; Requirements: Min 8 GB RAM; The code automatically utilizes GPUs if they are available, but it is designed to run on conventional laptops without specialized hardware.; awesome-llm-apps; Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, deep-learning; Also covers LLM Frameworks, Model Training; When you are interested in understanding the inner workings of large language models and want to build one from scratch using PyTorch.
- 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 quick and efficient way to deploy a pre-trained language model without delving into the implementation details. When you require a production-ready solution, as LLMs-from-scratch is primarily designed for educational purposes and may not be optimized for industrial use.
- 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 (136,444 vs 105,176). 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.