智谱发布GLM-5.3：开源的“安全之盾”
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Merged summary
TL;DR - Zhipu announced GLM-5.3, an open-weight model that uses substantially scaled post-training on the same base as GLM-5.2 to improve coding, agentic, and cybersecurity capabilities. Its weights are scheduled for release after two weeks of safety evaluation and hardening.
- GLM-5.3 reportedly leads open models on several coding and agent benchmarks, including Terminal-Bench 3.0 (28.3) and DeepSWE v1.1 (66.9).
- CyberGym vulnerability detection rose to 84.5%, while exploit-oriented results improved substantially but remained behind leading closed models.
- Zhipu attributes the gains entirely to longer, more diverse reinforcement-learning environments and extended post-training.
- The release includes layered misuse controls and an “Open Shield” program offering security-audit resources to open-source maintainers.
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智谱发布GLM-5.3：开源的“安全之盾”
Public signals
N/A
TL;DR - Zhipu announced GLM-5.3, an open-weight model that uses substantially scaled post-training on the same base as GLM-5.2 to improve coding, agentic, and cybersecurity capabilities. Its weights are scheduled for release after two weeks of safety evaluation and hardening.
- GLM-5.3 reportedly leads open models on several coding and agent benchmarks, including Terminal-Bench 3.0 (28.3) and DeepSWE v1.1 (66.9).
- CyberGym vulnerability detection rose to 84.5%, while exploit-oriented results improved substantially but remained behind leading closed models.
- Zhipu attributes the gains entirely to longer, more diverse reinforcement-learning environments and extended post-training.
- The release includes layered misuse controls and an “Open Shield” program offering security-audit resources to open-source maintainers.