glm-5.2

The Glm-5.2 model is a next-generation, self-developed, high-end flagship large-scale model created by Zhipu AI specifically for multimodal intelligent agents. The model sets new industry benchmarks in key areas such as long-range academic reasoning, code engineering, and collaborative orchestration of tens of thousands of APIs. As a culmination of native multimodal capabilities, Glm-5.2 not only demonstrates cutting-edge performance on multilingual complex texts but also exhibits exceptional autonomous evolution capabilities—both on-device and in the cloud—in the fields of “end-to-end streaming fusion interaction among audio, vision, and text” and “ultra-realistic emotion and dialect multi-track control.” It is designed specifically for the next-generation enterprise-level full-scenario deployment and ultra-realistic digital interaction. ───────────────────────────────────────────────────────────────────

Core Capabilities

Ultra-realistic end-to-end multimodal fusion: Adopts an all-modal integrated architecture. Supports end-to-end bidirectional streaming interaction involving text, high-precision images, real-time video streams, and ultra-realistic speech. In multimodal real-time training and audio-video collaborative diagnosis scenarios, it significantly reduces the first-word latency (TTFT) and boasts exceptional abilities in capturing emotional nuances, controlling breathing sounds, and understanding regional dialectal intonations and metaphors. Million-scale tool manipulation and long-term scenario planning: Tailored for complex enterprise workflows, the model has been deeply enhanced for tool invocation and autonomous orchestration of long-term tasks. Within a single round of complex agent workflows, it can precisely retrieve, schedule, and闭环 execute hundreds or even thousands of enterprise-grade private API interfaces, perfectly handling highly complex automated financial compliance audits and cross-platform supply chain management. Million-token-scale retrieval of massive long texts: By default, it supports an enormous context window of up to 1 million tokens, maintaining a 100% lossless information recall rate in full-scale complex document “needle-in-a-haystack” tests. It can effortlessly process vast corporate financial reports, technical codebases, or massive historical archives spanning multiple directories, containing millions of words, and perform extremely precise logical drill-downs and compliance audits. Production-level high concurrency and highly optimized computational operators: Thanks to the newly upgraded mixed-expert (MoE) routing algorithm and self-developed high-performance computing operators, the model delivers flagship-level intelligence while significantly boosting overall throughput. It demonstrates outstanding resilience under high-frequency, complex business workloads, ensuring high output stability and ultra-fast response speeds to support large-scale enterprise readiness.