Zhipu AI announced GLM-5.3, saying it is a post-training upgrade to GLM-5.2 with strong results on coding and cybersecurity tasks. The release timeline put Hugging Face open weights 2 weeks after the initial announcement, after starting with a coding plan and later expanding to an API. The model’s availability expands to API access and open weights while Zhipu stages broader cybersecurity releases via partner-only evaluation before publishing the weights.
Vals AI raised a $40 million Series A led by Andreessen Horowitz at a $400 million valuation to measure AI performance on real-world tasks. Its evaluation work includes automated, private test sets that are run in limited numbers, and it turns around results within hours of getting access to a new model. The funding and product launches (including Vals Smith, frontier-risk benchmarks, and Vals Index 2.0) expand its independent scoring infrastructure and broaden its measurement as models improve.
Z.ai released GLM-5.3 using the same 743B base model as GLM-5.2, improving it through scaled post-training rather than retraining the base. Terminal-Bench 3.0 increased from 4.6 to 28.3 and CyberGym rose from 77.2% to 84.5%. GLM-5.3 is partially deployable via the Z.ai API and coding products now, while weights are planned to be published about two weeks after launch after safety evaluation and hardening.
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