China report benchmarks LLM token-service performance
According to IT Home reports citing the joint publication, the China Academy of Information and Communications Technology's AI Research Institute, its Key Laboratory for Large Model and Software/Hardware Evaluation, and the China AI Industry Development Alliance released the 2026 LLM Token Service Performance Monitoring Report. Based on January-August monitoring data, it examines call success rate, throughput, time to first token, stability, price, context-window length and performance differences across official and third-party platforms. It reports that domestic daily token consumption reached about 500 trillion in June, while average domestic output throughput reached 78.23 tokens per second in August, compared with 38.25 for the 2025 average and 112.82 for typical foreign models.
The report says its comparisons can guide users in selecting model services and help the industry improve service capabilities. It also finds substantial performance variation for the same model across platforms, with throughput gaps approaching twofold.
IT之家 10 月 23 日消息，中国信息通信研究院（简称“中国信通院”）人工智能研究所、人工智能大模型及软硬件评测工业和信息化部重点实验室和中国人工智能产业发展联盟，今日（10 月 23 日）联合发布《大模型词元服务性能监测报告（2026 年）》。
报告称，随着大模型技术的迅速迭代，词元（Token）服务成为从技术走向应用的关键点，我国日均词元调用量持续攀升，2026 年 6 月，国内词元日均消耗量约 500 万亿，是 2025 年 12 月的近 4 倍。
产业中越来越多的 MaaS（Model as a Service，模型即服务）平台厂商通过公有云 API 方式供给大模型词元服务。然而用户对词元服务性能缺乏直观的判断依据，且面临选型困难等各类问题。
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