VibeThinker 3B - Taking on Giant Models
Skills:
Reading ML Papers80%
Key Takeaways
Analyzes VibeThinker 3B model performance and techniques for improving reasoning and chain of thought
Original Description
In this video, I look at VibeCoder 3b and how it is beating some models that are 300x its size on certain benchmarks by improving its reasoning and chain of thought to be better for specific use cases. While the model is not for production it shows what could be done with these techniques.
Thanks to Dell for Sponsoring the Compute
#DellProPrecision #DellProMax
Paper: https://arxiv.org/abs/2606.16140
Weights: https://huggingface.co/WeiboAI/VibeThinker-3B
Github: https://github.com/WeiboAI/VibeThinker
Twitter: https://x.com/Sam_Witteveen
🕵️ Interested in building LLM Agents? Fill out the form below
Building LLM Agents Form: https://drp.li/dIMes
👨💻Github:
https://github.com/samwit/llm-tutorials
⏱️Time Stamps:
00:00 Intro
01:16 VibeThinker-3B
03:33 Benchmarks
05:16 VibeThinker-3B Paper
05:46 Architecture
09:00 Demo
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Reading ML Papers
View skill →Related Reads
📰
📰
📰
📰
A lightweight workflow for keeping up with AI conference papers
Dev.to · Daniel
Why CitedEvidence Believes Great Researchers Read Less Than You Think
Medium · AI
How to Write a Literature Review That Actually Argues Something
Medium · Machine Learning
I Built a Personal Paper Engine to Stop Losing Research Papers
Dev.to · Ethan
Chapters (6)
Intro
1:16
VibeThinker-3B
3:33
Benchmarks
5:16
VibeThinker-3B Paper
5:46
Architecture
9:00
Demo
🎓
Tutor Explanation
DeepCamp AI