Nvidia's forgotten GPU became the most popular card on Steam, but not for the reason you'd think

Nvidia's RTX 3060 surge in Steam rankings, driven by its unexpected popularity for AI inference workloads rather than traditional gaming, highlights how consumer‑grade GPUs are being repurposed for large‑scale language model serving. For website owners, this shift means a new class of visitor traffic—AI‑driven bots and micro‑services that lease cheap RTX 3060 machines to run inference on models like LLaMA or Stable Diffusion. Unlike typical crawlers, these bots generate high‑frequency, data‑intensive requests (e.g., image generation, text completion APIs) that can strain bandwidth and skew analytics. Moreover, because the hardware is consumer‑grade, the bots often masquerade as ordinary browsers, making detection harder. **Actionable tips:** 1. **Update your llms.txt** to explicitly list the RTX 3060‑based inference services you permit (e.g., “OpenAI‑Lite‑RTX3060”, “StableDiffusion‑Node‑3060”) and deny all others, ensuring legitimate AI partners are recognized while unknown bots are blocked. 2. **Deploy behavior‑based bot tracking** that flags IPs with sustained high‑throughput POST requests to AI endpoints (e.g., `/api/v1/generate`). Combine this with User‑Agent heuristics that reference known RTX 3060 inference clients. 3. **Monitor resource usage spikes** in real time and set automated rate limits for identified AI traffic, preventing these cheap GPU farms from overwhelming your site while still allowing authorized AI services.