Empero AI has released Qwythos-9B-v2, an updated version of its large language model designed to eliminate looping and degeneration issues that previously affected a small percentage of its outputs. This new version achieves a 0% looping rate through a technique called Final-Token Preference Optimization, without sacrificing its 1 million token context window or reasoning capabilities. Internal benchmarks show that Qwythos-9B-v2 maintains or slightly improves performance on knowledge and reasoning tasks, though there is a minor decrease in coding benchmark scores. AI
IMPACT Enhances LLM reliability by fixing looping issues, potentially simplifying deployment for developers using long context windows.
RANK_REASON Model release from a lab (Empero AI) with a specific model name and version. [lever_c_demoted from frontier_release: ic=1 ai=1.0]
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