LLMs from Scratch vs 
Deep Learning Drizzle
LLMs from Scratch vs Deep Learning Drizzle compared for 2026 — features, license, ease of use, performance and which one to choose. Build a GPT from nothing, line by line vs University lectures, from the source.
Updated regularly · curated by OpenSourceAI.tech
LLMs from Scratch vs Deep Learning Drizzle at a glance
| Spec | LLMs from Scratch | Deep Learning Drizzle |
|---|---|---|
| Category | Learn AI & machine learning | Learn AI & machine learning |
| Type | Book + code | Lecture index |
| License | Apache-2.0 | MIT |
| Runs locally | Yes | Yes |
| Primary language | Python | Markdown |
| Ease of use | Intermediate | Advanced |
| Best for | genuinely understanding how an LLM works | learning from the actual researchers |
| GitHub stars | 99k | 12.8k |
How LLMs from Scratch and Deep Learning Drizzle score
| Criterion | LLMs from Scratch | Deep Learning Drizzle |
|---|---|---|
| Popularity | 4.5 | 3.0 |
| Maintenance | 5.0 | 2.0 |
| Ease of use | 3.5 | 2.5 |
| Privacy | 5.0 | 5.0 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
LLMs from Scratch
Sebastian Raschka's companion repository to "Build a Large Language Model (From Scratch)": you implement attention, a transformer, pretraining and fine-tuning yourself, in plain PyTorch.
- You build every component yourself — no black boxes
- Runs on a laptop, no cluster needed
- The clearest explanation of attention anywhere
Deep Learning Drizzle
An index of university lecture series on deep learning, NLP, computer vision and reinforcement learning — straight from Stanford, MIT, CMU, Oxford and others.
- Real university courses, not YouTube summaries
- Covers the theory most practical courses skip
- Slides and assignments included
Key differences
LLMs from Scratch is book + code, while Deep Learning Drizzle is lecture index. Their licenses differ (Apache-2.0 vs MIT), which matters if you ship a commercial product. LLMs from Scratch leans more intermediate-friendly, whereas Deep Learning Drizzle is more suited to advanced users. In short, LLMs from Scratch fits genuinely understanding how an LLM works, and Deep Learning Drizzle fits learning from the actual researchers.
Which should you choose?
Choose LLMs from Scratch for genuinely understanding how an LLM works. Choose Deep Learning Drizzle for learning from the actual researchers.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is LLMs from Scratch or Deep Learning Drizzle easier to use?
LLMs from Scratch is generally the easier of the two to get started with, while Deep Learning Drizzle rewards more setup with more control.
Are LLMs from Scratch and Deep Learning Drizzle free?
LLMs from Scratch is free and open source (Apache-2.0), and Deep Learning Drizzle is free and open source (MIT). Neither charges for the core software.
Can I run LLMs from Scratch and Deep Learning Drizzle locally?
LLMs from Scratch: yes · Deep Learning Drizzle: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
LLMs from Scratch vs Deep Learning Drizzle — which should I pick in 2026?
Choose LLMs from Scratch for genuinely understanding how an LLM works. Choose Deep Learning Drizzle for learning from the actual researchers.
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