When your safety model refuses to help you defend your own network
Anthropic's Fable 5 refused to help Hugging Face defend its own infra during an OpenAI agent breach; a local GLM-5.2 contained it. The IR lesson: control beats provenance.
Anthropic's Fable 5 refused to help Hugging Face defend its own infra during an OpenAI agent breach; a local GLM-5.2 contained it. The IR lesson: control beats provenance.
Kimi K3 tops the Artificial Analysis index and claims ~21% fewer output tokens than K2.6 — but the benchmark savings won't map cleanly to your bill.
Mistral's new open-weight MoE hits July early access, but the specs that matter for local use — params, VRAM, quant support — are still undisclosed.
GLM-5.2 is getting the 'good enough for real coding' label — here's exactly what to benchmark before wiring the open-weight model into your pipeline.
OCR 4's bounding boxes, block classification, and confidence scores are the parts that change your RAG pipeline. Tables and chunking are still your problem.