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GLM 5.2 Explained: Open-Weight Rival to GPT 5.5 + Benchmarks, Pricing, and a Live OpenCode Demo Try GLM 5.2 in OpenCode & Get $5 in Credits: https://opencode.ai/go?ref=M6HEHM4JM5 The video reviews GLM 5.2, ZAI’s latest flagship open-weight model, highlighting its competitiveness with closed frontier models like Opus 4.8 and GPT 5.5 across benchmarks, including cases where it outperforms GPT 5.5 and Fable 5. It covers key features such as a 1M-token context for long-horizon work, availability on Hugging Face under an MIT license, and deployment across multiple inference providers that can drive speed and lower prices. Using Artificial Analysis, the host discusses its intelligence index (~51), weighted cost per task (about $0.42 vs $0.83 for GPT 5.5 X-High), token usage patterns when “thinking” is increased, and typical per-token pricing. Benchmarks like Vending Bench and DeepSuite are discussed, followed by an OpenCode demo generating a SaaS landing page and commentary on output quality, plus speculation on timelines for a Fable-class model. 00:00 GLM 5.2 Overview 00:53 Access and Licensing 01:07 Intelligence Index and Open Weights 02:00 Cost and Token Efficiency 03:13 Vending Bench Surprise Win 04:17 Community Reactions and SVG Test 04:53 Model Specs and MoE 05:17 Coding Agent Benchmarks 05:56 Where to Use GLM 5.2 06:22 OpenCode Demo SaaS Page 07:18 Reviewing the Output 08:00 Future Model Timeline 08:39 Wrap Up and Questions
Technical content at the intersection of AI and development. Building with AI agents, Claude Code, and modern dev tools - then showing you exactly how it works.
