Keepace.ai: A Technical Report on a Large Language Model for Sports and Health
ai TeamBowen WuHeng WangJufeng MiKang LiuKun LiLing ManLong HeSuli FanXiaosen JiangYi WangYing HeYu TangYunhan LiZifang Liu
Nov 2026
Natural Language Processing
Abstract
Large language models hold promise for delivering safe, scientifically grounded, and personalized exercise guidance at scale, yet the sports-and-health domain still lacks curated training corpora and rigorous evaluation benchmarks. Keepace (Keepace.ai) is a domain-specialized LLM built on Qwen3.5-27B through post-training, currently optimized for Chinese-language exercise guidance across three tasks: workout plan generation, sports-and-health knowledge QA, and personal sports data analysis. In internal rubric-based evaluations designed with domain experts, Keepace outperforms its base model and larger general-purpose baselines, with the most pronounced improvements in exercise safety, boundary compliance, structured output completeness, and scientific accuracy. This report summarizes the current design, data pipeline, safety-first evaluation framework, and evaluation results of Keepace.
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