GLM-5.2 is an open-weight model that researchers claim matches Anthropic's Mythos on certain cybersecurity and bug-finding benchmarks, though it lags on general tasks.
Zhipu AI released its open-weight GLM-5.2 model, with researchers claiming it matches Anthropic's Mythos on certain bug-finding and cybersecurity tasks. The model lags behind Anthropic and OpenAI models on general benchmarks but represents a significant narrowing of capabilities between Chinese and US AI systems.
Zhipu AI's open-source GLM-5.2 model scores within one percentage point of Anthropic's Claude Opus 4.8 on a key agentic benchmark while costing approximately one-fifth as much. The release comes as U.S. government restrictions limit access to Anthropic's Fable and OpenAI's GPT-5.6 models.
Z.ai's GLM-5.2 performs on par with Claude Opus 4.8 and OpenAI's GPT-5.5 in cybersecurity benchmarks while costing roughly half as much to run. Security evaluations from Graphistry and Semgrep confirm the open-weight model's capabilities in vulnerability discovery and cyber investigation, raising concerns about accessibility of advanced hacking tools.
Z.ai released GLM-5.2 on June 16, 2026, the first open-weight model to match proprietary models like Claude Opus 4.8 on agent benchmarks. The MIT-licensed model closes the performance gap to 6.8 months behind frontier labs, down from expected 9+ months as compute scales.
Zhipu AI released GLM-5.2, a 753 billion parameter model with a 1 million token context window. The model scores 62.1% on SWE-bench Pro and introduces IndexShare architecture that reduces per-token FLOPs by 2.9× at 1M context length. Released under MIT license with no regional restrictions.
Z.AI has released GLM-5.2, an open-source model with a 1M-token context window under an MIT license. On FrontierSWE, a long-horizon coding benchmark, GLM-5.2 trails Claude Opus 4.8 by 1% while outperforming GPT-5.5 by 1%, and achieves 81.0 on Terminal-Bench 2.1 compared to Opus 4.8's 85.0.
Zhipu AI has released GLM-5.2, a 753 billion parameter model featuring a 1 million token context window and MIT open-source license. The model scores 62.1% on SWE-bench Pro and 91.2% on GPQA-Diamond, with flexible reasoning effort levels for coding tasks.
Z.ai has released GLM-5.2, a model designed for long-horizon engineering tasks with a 1 million token context window. The model is priced at $1.40 per million input tokens and $4.40 per million output tokens, and was released on June 16, 2025.