GLM 5.2

On June 17, 2026, Z.ai published the GLM 5.2 benchmark scorecard that was withheld at the June 13 launch, alongside MIT-licensed open weights for both zai-org/GLM-5.2 and zai-org/GLM-5.2-FP8 on HuggingFace — arriving earlier than the originally promised "the following week" timeline. GLM 5.2 posts 62.1 on SWE-bench Pro The article frames GLM 5.2 as the first credibly open-weight model to lead an Anthropic or OpenAI flagship on a real-world SWE-bench Pro head-to-head, noting that teams using Claude Code, the Claude Agent SDK, Cursor, or the Vercel AI Gateway now have a frontier-tier open-weight backend they can self-host. It also reca

ThursdAI's June 2026 monthly roundup lists GLM-5.2 as one of 32 AI releases covered that month, attributing it to Z.ai (Zhipu AI) and categorizing it for developers and coding agents. The aggregator reports concrete model-intrinsic specs: a 753-billion-parameter open Mixture-of-Experts architecture and a 1M-token conte As a secondary podcast/newsletter aggregator, ThursdAI corroborates Z.ai authorship and the 753B open-MoE / 1M-context framing, but its single-source GPQA Diamond figure and other benchmark numbers are not independently verified against a Z.ai release post or model card within this candidate set. The roundup neverthele

Z.ai (formerly Zhipu AI / THUDM) released GLM-5.2 on June 13, 2026, as a 744-billion-parameter open-weight Mixture-of-Experts model under the MIT license, activating roughly 40B parameters per token across 384 experts and supporting a 1,000,000-token context window with a 131,072-token maximum output. The article docum Technically, GLM-5.2 introduces IndexShare sparse attention, which the source cites as achieving a 2.9x FLOP reduction at the full 1M context length, along with an improved Multi-Token Prediction speculative decoding path. The model uses a higher activation ratio than Kimi K2.7, and the article walks through local depl

Simon Willison's hands-on review from June 17, 2026 describes GLM-5.2 as Z.ai's 753B-parameter Mixture-of-Experts model with 40 active parameters per token, a ~1.51TB checkpoint, text-only input, and an MIT-licensed open-weights release on June 16, 2026 (after a coding-plan soft launch on June 13). The context window i Willison notes GLM-5.2 is token-hungry at roughly 43k output tokens per Intelligence Index task and ranks #2 on the Code Arena WebDev leaderboard behind Claude Fable 5. He accessed the model through OpenRouter, where nine providers list it at approximately $1.40 per million input tokens and $4.40 per million output tok

The U.S. National Institute of Standards and Technology's Center for AI Standards and Innovation (CAISI) published an independent assessment of Z.ai's open-weight GLM-5.2 model on July 8, 2026, roughly three weeks after its June 16, 2026 release. CAISI concluded that GLM-5.2 was probably the most capable open-weight AI On safeguards and security, CAISI found mixed results: GLM-5.2's safeguards permitted assistance with agentic cyber exploit development and blocked fewer sensitive biological questions than reference U.S. models, but it appeared potentially more robust than other evaluated PRC open-weight models against agent-hijacking

A Hacker News discussion (916 points, ~80 days old) centered on Artificial Analysis's leaderboard post declaring GLM-5.2 the new leading open-weights model. Commenters provide concrete behavioral observations: GLM 5.2 supports reasoning-effort tiers ("high" and "xhigh," with xhigh mapped to max effort), and at xhigh it The thread frames GLM 5.2 as a significant step up for open weights and getting close to frontier, while flagging reasoning efficiency as the next bottleneck relative to GPT 5.5. It also reinforces Z.ai's open-weights positioning by emphasizing the cost gap (GLM 5.2 expected to undercut Opus 4.8 and GPT 5.5 on price ev