VibeThinker-3B: Small AI model competes with larger ones via reasoning compression | Factae🤖VibeThinker-3B: Small AI model competes with larger ones via reasoning compression
Sina Weibo's VibeThinker-3B (3B parameters) matches performance of models 333x larger (DeepSeek V3.2, Kimi K2.5) in math and coding benchmarks.
Published 2sem·1 sourceNotable
The fact
Its efficiency stems from multi-stage post-training, focusing on compressing logical reasoning rather than factual knowledge.
Researchers propose that reasoning compresses better than broad world knowledge in small models.
🔗Click the link to read the original article:
Today's news on Factae→Auto-synthesis from 1 media source · identified on June 28, 2026