Leaked R&D records reveal Zhipu is conducting end-to-end programming post-training on 32B, 122B, and 256B models for GLM-5.5, targeting 100% recursive self-improvement via coding agents, a 100T token dataset goal, and new scale-correctness validation methods.
Renowned security researcher Yuki Chen joins Zhipu AI and demonstrates using the GLM model to discover Windows vulnerabilities, earning 23 Microsoft MSRC acknowledgments; NIST and Anthropic benchmarks show GLM-5.3 leads open-weight models in cybersecurity tasks but trails frontier models by about four months.
In 2026, leading AI labs demonstrate measurable recursive self-improvement: Anthropic reports 80% of code written by Claude and 26% of R&D led by AI, OpenAI achieves 3.1 agent-days per human day, while Zhipu and MiniMax close engineering loops; yet Princeton's shadow evaluation rejects AI-authored papers, safety incidents reveal structural risks, and the R_AI metric suggests true intelligence explosion remains unproven.
Zhipu AI's GLM-5.3-FlashX achieves 200 tokens/s, a 5x speedup over Flash, built on 100k domestic chips using Agent-driven dense feedback loops that optimize the full inference pipeline through three case studies: FP32/TF32 precision fixes, GIL contention in KV Transfer, and redundant computation elimination in KDA Decode.
On May 22 2026, Zhipu AI released the GLM‑5.1‑HighSpeed variant, which generates up to 400 tokens per second—over six times the speed of the standard GLM‑5.1 and twice that of Google’s Gemini‑3.5‑Flash—thanks to multi‑dimensional inference, attention and sequence‑parallel optimizations while preserving full model capabilities.
This guide walks you through the minimal steps required to install and configure Claude Code on macOS, covering prerequisite tools, CLI installation, API‑key setup with Zhipu AI, and best‑practice directory structures for seamless, context‑aware AI coding.
The author demonstrates a voice‑driven workflow that combines Gemini CLI, the Zhipu AI input method, and Obsidian, showing step‑by‑step how to launch commands, monitor the terminal, manage files, generate content, and automate routine tasks with spoken prompts.
This guide walks you through building an n8n workflow that automatically generates hand‑drawn doodle‑style covers for Xiaohongshu posts by configuring Volcano Engine and Zhipu AI services, creating API keys, and chaining chat, prompt, HTTP, and download nodes into a seamless design pipeline.
This article explains how to integrate a large‑model AI service by constructing the standard HTTP request payload with system, user, and assistant messages, details the key request parameters, and shows how to parse the non‑streaming and streaming response structures using the Zhipu AI Node.js SDK.
On May 16, 360 and Zhipu AI announced a strategic partnership to co‑develop the trillion‑parameter models 360GLM and 360GPT, positioning them as China’s answer to Microsoft‑OpenAI by combining large‑scale pre‑training, bilingual capabilities, and integration with 360’s search and browser ecosystem.
