Understanding Reasoning LLMs
Read OriginalThis technical article defines reasoning models and details four key methods to build them: inference-time scaling, pure reinforcement learning, SFT+RL, and pure supervised fine-tuning. It discusses the specialization of LLMs for complex, multi-step tasks like coding and math, using examples like the DeepSeek training pipeline, and provides guidance on when to use reasoning models.
Comments
No comments yet
Be the first to share your thoughts!
Browser Extension
Get instant access to AllDevBlogs from your browser
Top of the Week
1
Quoting Thariq Shihipar
Simon Willison
•
2 votes
2
The Beautiful Web
Jens Oliver Meiert
•
1 votes
3
Container queries are rad AF!
Chris Ferdinandi
•
1 votes
4
Top picks — 2026 January
Paweł Grzybek
•
1 votes
5
In Praise of –dry-run
Henrik Warne
•
1 votes
6
Deep Learning is Powerful Because It Makes Hard Things Easy - Reflections 10 Years On
Ferenc Huszár
•
1 votes
7
Vibe coding your first iOS app
William Denniss
•
1 votes
8
AGI, ASI, A*I – Do we have all we need to get there?
John D. Cook
•
1 votes
9
How to Add a Quick Interactive Map to your Website
Miguel Grinberg
•
1 votes