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Model: "gpt-5.2-codex"
not much happened today.
gpt-5.2-codex glm-4.7 openai cursor github cerebras modal artificial-analysis vllm long-running-tasks autonomous-agents code-generation inference-speed latency batch-inference gpu-scaling model-evaluation agent-systems operational-scaling swyx kevinweil pierceboggan mntruell scaling01
OpenAI launched GPT-5.2-Codex API, touted as their strongest coding model for long-running tasks and cybersecurity. Cursor integrated GPT-5.2-Codex to autonomously run a browser for a week, producing over 3 million lines of Rust code. GitHub incorporated it into their code tools, easing enterprise adoption. Discussions highlight the importance of review loops in agent systems and debate evaluation metrics for coding models. OpenAI partnered with Cerebras to improve inference speed and latency, with Cerebras serving GLM-4.7 at 1,445 tokens/sec and low latency. Provider benchmarking reveals tradeoffs in throughput, latency, and context window sizes. Modal shared operational scaling insights for self-hosted inference fleets of 20k GPUs, focusing on batch inference optimization with vLLM and FlashInfer backend. This reflects a focus on inference infrastructure, long-horizon autonomous agents, and coding model evaluation.
Claude Skills grows: Open Standard, Directory, Org Admin
claude-skills gpt-5.2-codex gemini-3-flash functiongemma t5gemma-2 anthropic openai google-deepmind hugging-face agentic-ai fine-tuning long-context tool-calling on-device-ai multimodality security workflow-optimization sama gregbrockman philschmid
Claude Skills are gaining significant traction since their launch in October, with a milestone of 100k views in one day for the Claude Skills talk, signaling growing adoption and importance. Announcements include org admin support, a new Skills Directory, and the move to an open standard named Agent Skills. In frontier model launches, OpenAI released GPT-5.2-Codex, touted as the best agentic coding model with improvements in native compaction, long-context reliability, and tool-calling, emphasizing real-world security impacts. Google DeepMind introduced Gemini 3 Flash, focusing on speed as a product feature impacting workflows and user engagement, alongside FunctionGemma and T5Gemma 2, emphasizing on-device deployment, fine-tuning, and multimodality.