DeepPrinciple just dropped Hydrogen-1.0, an open-weight, 753-billion-parameter model designed for chemistry, materials science, and biology. Fine-tuned on real laboratory workflows, it can write and self-debug simulation code, decipher NMR spectra, and compile protocols directly for lab automation. It even matches or outperforms GPT-6-Astra on several core scientific benchmarks.
Anthropic just published a red-team evaluation of Zhipu AI's open-weight GLM-5.3, revealing that it can autonomously develop end-to-end cyberexploits on par with Claude Mythos Preview. Even worse, researchers bypassed its safeguards up to 100% of the time, dropping refusal rates to roughly 2% for just $4,400 in compute. Why it matters: Frontier-level offensive cyber tools are now freely downloadable with virtually zero effective restrictions.
ZAI just open-sourced the full model weights for GLM-5.3 on Hugging Face, packing 753 billion parameters focused on heavy coding and complex agent workflows. It uses the same base model as GLM-5.2, squeezing every performance gain out of pure post-training to rival top commercial models. Community-quantized GGUF versions are already out for local multi-GPU setups.
Z.ai just launched its GLM-5.3 API, custom-built for coding, defensive cybersecurity, and long-horizon agentic tasks. Best of all, it keeps the exact same pricing as GLM-5.2, meaning developers can upgrade their automated workflows with zero extra cost. It is available right now via Z.ai's official API and partner model gateways.
Z.ai just released GLM-5.3, a coding-focused model that achieves open-weights SOTA on Terminal Bench 3.0 and Agents' Last Exam purely through post-training scaling. Unexpectedly, the model more than doubled its cyber exploitation scores, uncovering 2,436 real-world vulnerabilities dating back up to 40 years. Model weights will drop in two weeks after a safety review.
