Brief

VibeThinker-3B is a newly released dense 3B-parameter model (announced 2026-06-16) claiming frontier-level verifiable reasoning with strong benchmarks (94.3 AIME’26; 76.4 IMO-AnsBench; 80.2 Pass@1 LCB v6, improved with CLR). It also reports 96.1% first-attempt Python pass rate on unseen LeetCode weekly contests and promotes small verification-focused models as a complementary path to scaling laws.

⭐ VibeThinker-3B is released — a dense 3B model for frontier-level verifiable reasoning.

🚀 Reasoning: 94.3 on AIME’26, 76.4 on IMO-AnsBench, and 80.2 Pass@1 on LCB v6; with CLR, AIME‘26 improves to 97.1 and IMO-AnsBench to 80.6.

💻 OOD Coding: On recent unseen LeetCode weekly contests, VibeThinker-3B passes 123/128 (96.1%) first-attempt Python submissions.

⚡ Efficiency: Only 3B parameters, yet reaching the performance range of much larger top-tier reasoning models.

🧠 Perspective: Small models are not just cheaper substitutes. In parameter-dense domains with clear verification signals, SLMs offer a path to frontier-level reasoning that complements traditional Scaling Law.

Model : huggingface.co/WeiboAI/VibeT…
Github: github.com/WeiboAI/VibeThink…
Paper: huggingface.co/papers/2606.1…

AI #LLM #Reasoning #OpenSource #SmallModel