Dive into Deep Learning vs 
Awesome LLM
Dive into Deep Learning vs Awesome LLM compared for 2026 — features, license, ease of use, performance and which one to choose. The textbook where every equation is runnable vs Papers, models and tools of the LLM era.
Updated regularly · curated by OpenSourceAI.tech
Dive into Deep Learning vs Awesome LLM at a glance
| Spec | Dive into Deep Learning | Awesome LLM |
|---|---|---|
| Category | Learn AI & machine learning | Learn AI & machine learning |
| Type | Interactive book | Curated list |
| License | CC-BY-SA-4.0 | CC0-1.0 |
| Runs locally | Yes | Yes |
| Primary language | Jupyter | Markdown |
| Ease of use | Intermediate | Beginner |
| Best for | a rigorous foundation you can actually execute | getting your bearings in the LLM landscape |
| GitHub stars | 29.2k | 27.1k |
How Dive into Deep Learning and Awesome LLM score
| Criterion | Dive into Deep Learning | Awesome LLM |
|---|---|---|
| Popularity | 3.5 | 3.5 |
| Maintenance | 2.0 | 3.0 |
| Ease of use | 3.5 | 5.0 |
| Privacy | 5.0 | 5.0 |
| License freedom | 3.5 | 3.5 |
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
Dive into Deep Learning
An open textbook used in 500+ universities: every concept comes with maths, runnable code and exercises, available for PyTorch, TensorFlow, JAX and MXNet.
- Adopted by 500+ universities worldwide
- Every equation has runnable code beside it
- Works with PyTorch, TensorFlow and JAX
Awesome LLM
A curated index of the LLM landscape: the foundational papers, the open models, the training and serving tools — updated as the field moves.
- Tracks papers, models and tools in one place
- Updated as the field moves
- Good entry point into the research
Key differences
Dive into Deep Learning is interactive book, while Awesome LLM is curated list. Their licenses differ (CC-BY-SA-4.0 vs CC0-1.0), which matters if you ship a commercial product. Dive into Deep Learning leans more intermediate-friendly, whereas Awesome LLM is more suited to beginner users. In short, Dive into Deep Learning fits a rigorous foundation you can actually execute, and Awesome LLM fits getting your bearings in the LLM landscape.
Which should you choose?
Choose Dive into Deep Learning for a rigorous foundation you can actually execute. Choose Awesome LLM for getting your bearings in the LLM landscape.
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 Dive into Deep Learning or Awesome LLM easier to use?
Awesome LLM is generally the easier of the two to get started with, while Dive into Deep Learning rewards more setup with more control.
Are Dive into Deep Learning and Awesome LLM free?
Dive into Deep Learning is free and open source (CC-BY-SA-4.0), and Awesome LLM is free and open source (CC0-1.0). Neither charges for the core software.
Can I run Dive into Deep Learning and Awesome LLM locally?
Dive into Deep Learning: yes · Awesome LLM: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
Dive into Deep Learning vs Awesome LLM — which should I pick in 2026?
Choose Dive into Deep Learning for a rigorous foundation you can actually execute. Choose Awesome LLM for getting your bearings in the LLM landscape.
People also compare
Explore more open-source AI
Browse thousands of open-source AI tools, models and projects — all curated in one place, updated daily.
Explore the directory →