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Two professionals examine performance graphs on a monitor in a data center with NVIDIA servers.

Benchmarking LLM Performance at Scale with NVIDIA AIPerf

You're deploying a model on a system. It starts up, prompts are getting responses. Now the hard question: Is this fast? Your instincts might lead you to send curl commands, hand-roll an asyncio script, or write yet another one-off load generator. All these approaches share the same problems: single-process performance limits, Python's GIL capping concurrency, or numbers measured against a reference you built yourself. Either way, you end up with results you can't fully trust, attached to tooling you'll have to rewrite the moment requirements change. What you need is a load client that can...

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Understanding YOLO Mode: How to Give AI Agents Freedom Safely

Understanding YOLO Mode: How to Give AI Agents Freedom Safely

AI agents have grown significantly in capability and adoption since generative AI went mainstream in late 2022. In Stack Overflow's 2025 Developer Survey, 84% of developers said they use or plan to use AI tools in their workflow, up from 76% a year earlier. As these tools shift from suggesting code to writing files and running commands autonomously, a practical question emerges: How much should an agent be allowed to do without stopping to ask? Developers call the extreme end of this spectrum YOLO mode. Understanding YOLO mode before enabling it is important, but the main risk is often...

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