VibeThinker 3B 🚨 1.This model was not trained on tool calling or agent based programming data. We therefore do not recommend using it for tasks that involve function calling, API orchestration, or autonomous coding agents. For programming tasks, we recommend using this model on competitive programming problems (e.g., LeetCode style ). 2.For harder math reasoning, try AMOBench , a problem set harder than the International Mathematical Olympiad (IMO), with included standard answers. Use it to evaluate VibeThinker against other SOTA models. Note: due to extreme difficulty, set max tokens to 60K–100K. GitHub ModelScope Technical Report Introduction VibeThinker 3B is a further exploration of the VibeThinker series at the 3B parameter scale, focusing on challenging reasoning tasks with clear verification signals, such as mathematics, coding, and STEM. By systematically optimizing the Spectrum to Signal Principle (SSP) post training pipeline introduced in VibeThinker 1.5B, VibeThinker 3B achieves strong performance on AIME, HMMT, IMO AnswerBench, LiveCodeBench, and recent LeetCode contests, reaching the performance range of top tier fro…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy