Artificial Analysis — an independent AI model evaluation platform — published (X/Twitter thread from June 22, 2026 + detailed model page) a comparison placing GLM-5.2, the latest model from Z.ai (Zhipu AI), at the top of open weights models and #3 in the overall ranking of GDPval-AA. This benchmark measures performance on real-world, economically valuable knowledge work, through long-horizon and multi-turn tasks, designed as genuine professional tests (for example, a retail store supervisor's daily task list, or an IEC technical document) covering both professional and creative work.
GLM-5.2 scores 1524 Elo, behind only Claude Fable 5 (1783) and Claude Opus 4.8 (1615), and on par with GPT-5.5 in xhigh setting (1509). More importantly, it dominates the open-weights field by a wide margin: the next-best open model, MiniMax-M3, scores only 1408. GLM-5.2 also outperforms several proprietary models — Gemini 3.5 Flash (1357), Qwen 3.7 Max (1289), and Muse Spark (1158).
The agentic nature of the tasks is emphasized: GLM-5.2 averaged ~31 turns per task across 1,999 matches. Artificial Analysis's methodology consists of giving the same briefs to GLM-5.2 and three proprietary frontier models (Fable 5, GPT-5.5, Gemini 3.5 Flash), then rendering each deliverable exactly as produced. The result is consistent across the company's own indices: GLM-5.2 is #1 among open weights on the Intelligence Index, #3 on the Agentic Index, and #3 on AA-Briefcase (where it is the top open model, ahead of GPT-5.5 xhigh and behind only Fable 5).
The model page rounds out the picture: GLM-5.2 is a Mixture of Experts with 753 billion parameters (of which 40 billion active), a reasoning model with 1M token context, distributed under MIT license (commercial use allowed, weights on Hugging Face), released on June 16, 2026. On the economics side: $1.40 / $4.40 per million tokens (input/output), a cache-hit rate of $0.26 (-81%), a throughput of 106.3 tokens/s, and a time to first token of 1.36s.
The message conveyed by the numbers is clear: that an open weights model at this price rivals the proprietary frontier on genuinely useful agentic work constitutes, according to Artificial Analysis, "a real step for open models." The open/proprietary convergence is no longer just about academic tests, but about the economic value produced under agentic conditions.