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
source
