QED-Nano: what a 4B model can teach us about mathematical proofs
A post published on February 15, 2026 presents QED-Nano, a project to train a 4-billion-parameter model to prove olympiad problems, with material on training, datasets, and implementation.
Source: QED-Nano: Treinando um modelo de 4B para provar problemas de olimpíada (huggingface.co). Text prepared with AI from this source.
What happened and what to do
The post about QED-Nano describes a project to teach a 4-billion-parameter model to prove difficult olympiad problems. Published on February 15, 2026, it covers training, datasets, and implementation, and points to a collection and the project code.
A company could use this approach as a starting point for evaluating reasoning systems in its own domain: assemble examples and evaluation criteria, automate tests, and track errors and performance in a dashboard. Whether to adapt a model, integrate a proof tool, or retain a rule-based process depends on requirements and an initial assessment.
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Wendelmaques can diagnose the opportunity and requirements, define a scoped implementation for data collection, evaluation, and monitoring, and support its operation on the company’s infrastructure.
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