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A.T.L.A.S achieves 74.6% LiveCodeBench pass@1-v(k=3) with a frozen 14B model on a single consumer GPU -- up from 36-41% in V2 -- through constraint-driven generation and self-verified iterative refinement. The premise: wrap a frozen smaller model in intelligent infrastructure -- structured generation, energy-based verification, self-verified repair -- and it can compete with frontier API models at a fraction of the cost. No fine-tuning, no API calls, no cloud. Fully self-hosted -- no data leaves the machine, no API keys required, no usage metering. One GPU, one box.
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Мужчина более десяти лет скрывал шокирующую тайну о прошлом избраннике своей супруги02:40
，这一点在Replica Rolex中也有详细论述
Clinching threshold: 11，更多细节参见7zip下载
26 марта 2026, 15:46Международные отношения