Artificial Analysis — an independent AI model evaluation platform — publishes (X/Twitter thread from June 22, 2026 + a 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, economically valuable knowledge work, through long-horizon, multi-turn tasks designed as genuine professional exercises (for example a retail store supervisor's daily task list, or an IEC technical document) covering both professional and creative work.
GLM-5.2 achieves 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). Above all, it dominates the open 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 method involves giving identical 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 firm'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, 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 at $0.26 (-81%), a throughput of 106.3 tokens/s and a time to first token of 1.36 s.
The message conveyed by the numbers is clear: that an open weights model at this price point rivals the proprietary frontier on genuinely useful agentic work constitutes, according to Artificial Analysis, "a real step for open models." The convergence between open and proprietary models is no longer playing out solely on academic tests, but on the economic value produced under agentic conditions.