Comparison
LLMs-from-scratch vs ai-engineering-from-scratch
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 ai-engineering-from-scratch if ai-engineering-from-scratch is a comprehensive course that teaches AI engineering skills from foundational math to advanced AI agents and machine learning techniques, using Python and Node.js for interactive learning and.
Markdown twin · LLMs-from-scratch alternatives · ai-engineering-from-scratch alternatives
GraphCanon updated Sep 20, 2026
17views this month
vs
Trust & integrity
| Signal | LLMs-from-scratch | ai-engineering-from-scratch |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Active (10d since push) As of Sep 18, 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 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | Published findings As of Sep 18, 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
- ai-engineering-from-scratch
- Learn, build, and deploy AI engineering skills from scratch.
Stars
- LLMs-from-scratch
- 105k
- ai-engineering-from-scratch
- 55k
Forks
- LLMs-from-scratch
- 16k
- ai-engineering-from-scratch
- 9.6k
Open issues
- LLMs-from-scratch
- 2
- ai-engineering-from-scratch
- 114
Language
- LLMs-from-scratch
- Jupyter Notebook
- ai-engineering-from-scratch
- 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.
- ai-engineering-from-scratch
- ai-engineering-from-scratch is a comprehensive course that teaches AI engineering skills from foundational math to advanced AI agents and machine learning techniques, using Python and Node.js for interactive learning and
Persona
- LLMs-from-scratch
- -
- ai-engineering-from-scratch
- -
Runtime
- LLMs-from-scratch
- -
- ai-engineering-from-scratch
- -
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.
- ai-engineering-from-scratch
- MIT
Last pushed
- LLMs-from-scratch
- Sep 17, 2026
- ai-engineering-from-scratch
- Sep 7, 2026
Categories
- LLMs-from-scratch
- LLM Frameworks, Model Training
- ai-engineering-from-scratch
- AI Agents, Computer Vision, Developer Tools, Model Training
Trust and health
Maintenance
- LLMs-from-scratch
- Very active (96%)
- ai-engineering-from-scratch
- Active (82%)
Days since push
- LLMs-from-scratch
- 0d
- ai-engineering-from-scratch
- 10d
Open issues (now)
- LLMs-from-scratch
- 2
- ai-engineering-from-scratch
- 114
Stars delta
- LLMs-from-scratch
- +2.4k (30d)
- ai-engineering-from-scratch
- +8.1k (30d)
Open issues delta
- LLMs-from-scratch
- 0 (30d)
- ai-engineering-from-scratch
- +7 (30d)
Full report
- LLMs-from-scratch
- Trust report
- ai-engineering-from-scratch
- Trust report
Typed relationship
LLMs-from-scratch alternative ai-engineering-from-scratch'ai-engineering-from-scratch' and 'LLMs-from-scratch' both aim at teaching how to build AI models from scratch, though they have a focus on different sets of tools or methods.
Choose LLMs-from-scratch if…
- LLMs-from-scratch is primarily Jupyter Notebook; ai-engineering-from-scratch is Python.
- License: LLMs-from-scratch is Other, ai-engineering-from-scratch is MIT.
- 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..
- 'ai-engineering-from-scratch' and 'LLMs-from-scratch' both aim at teaching how to build AI models from scratch, though they have a focus on different sets of tools or methods.
- Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, finetuning.
- Also covers LLM Frameworks.
- 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 ai-engineering-from-scratch if…
- ai-engineering-from-scratch is primarily Python; LLMs-from-scratch is Jupyter Notebook.
- License: ai-engineering-from-scratch is MIT, LLMs-from-scratch is Other.
- 'ai-engineering-from-scratch' and 'LLMs-from-scratch' both aim at teaching how to build AI models from scratch, though they have a focus on different sets of tools or methods.
- Tags unique to ai-engineering-from-scratch: agents, ai-engineering, computer-vision, from-scratch.
- Also covers AI Agents, Computer Vision, Developer Tools.
- when you need a structured course that covers a wide range of AI engineering topics from scratch, including foundational math, deep learning, and reinforcement learning.
When NOT to use ai-engineering-from-scratch
- if you are looking for a tool that focuses solely on theoretical knowledge without practical application, as this course emphasizes hands-on learning.
- when you do not have access to Node.js or Python, as these are required for running the course and its interactive components.
- if you prefer a more traditional learning approach without the use of terminal-based learning tools, as the course is designed for interactive terminal sessions.
- when you are working with a development environment that does not support skill-capable hosts, as the course is optimized for such environments.
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 (rohitg00/ai-engineering-from-scratch) · observed Sep 20, 2026
- GitHub forks (rohitg00/ai-engineering-from-scratch) · observed Sep 20, 2026
- Last push (rohitg00/ai-engineering-from-scratch) · observed Sep 7, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: LLMs-from-scratch 105k · ai-engineering-from-scratch 55k (synced Sep 20, 2026).
Common questions
- What is the difference between LLMs-from-scratch and ai-engineering-from-scratch?
- LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step. ai-engineering-from-scratch: Learn, build, and deploy AI engineering skills from scratch.. See the comparison table for live GitHub stats and shared categories.
- When should I choose LLMs-from-scratch over ai-engineering-from-scratch?
- Choose LLMs-from-scratch over ai-engineering-from-scratch when LLMs-from-scratch is primarily Jupyter Notebook; ai-engineering-from-scratch is Python; License: LLMs-from-scratch is Other, ai-engineering-from-scratch is MIT; 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.; 'ai-engineering-from-scratch' and 'LLMs-from-scratch' both aim at teaching how to build AI models from scratch, though they have a focus on different sets of tools or methods; Tags unique to LLMs-from-scratch: ai, artificial-intelligence, attention-mechanism, finetuning; Also covers LLM Frameworks; 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 ai-engineering-from-scratch over LLMs-from-scratch?
- Choose ai-engineering-from-scratch over LLMs-from-scratch when ai-engineering-from-scratch is primarily Python; LLMs-from-scratch is Jupyter Notebook; License: ai-engineering-from-scratch is MIT, LLMs-from-scratch is Other; 'ai-engineering-from-scratch' and 'LLMs-from-scratch' both aim at teaching how to build AI models from scratch, though they have a focus on different sets of tools or methods; Tags unique to ai-engineering-from-scratch: agents, ai-engineering, computer-vision, from-scratch; Also covers AI Agents, Computer Vision, Developer Tools; when you need a structured course that covers a wide range of AI engineering topics from scratch, including foundational math, deep learning, and reinforcement learning.
- 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 ai-engineering-from-scratch?
- if you are looking for a tool that focuses solely on theoretical knowledge without practical application, as this course emphasizes hands-on learning. when you do not have access to Node.js or Python, as these are required for running the course and its interactive components. if you prefer a more traditional learning approach without the use of terminal-based learning tools, as the course is designed for interactive terminal sessions. when you are working with a development environment that does not support skill-capable hosts, as the course is optimized for such environments.
- Is LLMs-from-scratch or ai-engineering-from-scratch more popular on GitHub?
- LLMs-from-scratch has more GitHub stars (105,176 vs 54,935). Stars measure visibility, not whether either tool fits your constraints.
- Are LLMs-from-scratch and ai-engineering-from-scratch open source?
- Yes - both are open-source projects on GitHub (LLMs-from-scratch: Other, ai-engineering-from-scratch: MIT).
- Where can I find alternatives to LLMs-from-scratch or ai-engineering-from-scratch?
- GraphCanon lists graph-backed alternatives at LLMs-from-scratch alternatives and ai-engineering-from-scratch alternatives (LLMs-from-scratch markdown twin, ai-engineering-from-scratch 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 ai-engineering-from-scratch?
- LLMs-from-scratch: Very active. ai-engineering-from-scratch: 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 ai-engineering-from-scratch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLMs-from-scratch trust report; ai-engineering-from-scratch trust report.