Topic
Z AI
4 episodes
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Z.ai Launches GLM 5.2 With a Usable 1M Token Context, Two Thinking Effort Levels, and No Benchmarks at Launch
Z.ai launches GLM-5.2 with a usable 1M-token context window, two thinking-effort levels (High and Max), and same-day availability across all Coding Plan tiers. The 5x jump from GLM-5.1's 200K window lets coding agents hold entire mid-sized repositories in working memory without constant summarization. Setup is a drop-in swap (base URL + model ID) for Claude Code, Cline, and OpenClaw. Critical caveat: Z.ai published zero benchmarks at launch — no SWE-bench, Terminal-Bench, or Code Arena scores. The 744B MoE backbone (40B active params) is unchanged from GLM-5 lineage; all gains are post-training and context engineering.
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AI joins the 8 hour work day as GLM ships 5.1 open source LLM, beating Opus 4.6 and GPT 5.4 on SWE Bench Pro
Discussion of GLM-5.1, a new open-source large language model that can work autonomously for up to eight hours on a single task, and its implications on the AI industry
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z.ai debuts faster, cheaper GLM 5 Turbo model for agents and 'claws' — but it's not open Source
Z.ai launches GLM-5-Turbo, a proprietary variant of their open-source GLM-5 model optimized for agent workflows and tool use. At $4.16 per million tokens total cost, it undercuts competitors while delivering better tool reliability and execution stability for multi-step automation tasks.
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z.ai's open source GLM 5 achieves record low hallucination rate and leverages new RL 'slime' technique
z.ai's GLM-5 achieves record-low hallucination rates using a novel 'slime' reinforcement learning technique, scaling to 744B parameters while undercutting competitors by 6x on pricing. The model features native document generation and Agent Mode capabilities for enterprise workflows.