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VibeThinker-3B reaches frontier math and coding performance at small scale

A 3 billion parameter model trained for verifiable reasoning achieves 94.3% on AIME and 96.1% on unseen LeetCode contests, challenging the assumption that frontier performance requires massive scale.

1 min read

VibeThinker-3B, an open-source small language model, has achieved frontier-level performance on mathematics and coding benchmarks with only 3 billion parameters. The model scores 94.3 on AIME'26, 80.2 on LiveCodeBench v6, 76.4 on IMO-AnswerBench, and 93.4 on IFEval, according to results shared on Re...

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Method & sources
Source type
Primary publication (lab/vendor blog) — our analysis + implication
Source link
r/localllama
Published
UTC
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By the gotcontext.ai team (editorial standards)
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