GeForce RTX 3060, RTX 5050 split AI buyers

This is a VRAM question disguised as a price question. Inference: the higher 3060 price is the market pricing in its AI usefulness, not its gaming performance.

• –NVIDIA's specs show the RTX 5050 at 8GB and 128-bit, while the RTX 3060 family includes a 12GB / 192-bit config that is much harder to outgrow.
• –For local AI, memory capacity usually matters before raw generation features; once models, context, and tooling stack up, 8GB gets cramped fast.
• –The 5050's Blackwell features, DLSS 4, and 5th-gen Tensor Cores make it the cleaner gaming-first choice, but they do little for beginner ML throughput.
• –The Reddit consensus is practical: buy the most VRAM you can reasonably afford, because that buys room for quantized LLMs, embeddings, and experimentation.
• –If the goal is to learn RAG, agents, and local LLM basics, the 3060 is the more durable pick; if gaming dominates, the 5050 is the cheaper, newer alternative.