> That really depends on the model, I run a few models locally. All at speeds comparable to or faster than Opus.

Yes, a lot of Qwen3.8 27B setups are actually quite snappy, as long as they fit 100% in VRAM. In my testing, I wouldn't go below 32GB of VRAM, though—you really want a 6-bit quant and 8-bit K/V quants minimum. I've seen too much weirdness out of 4-bit quants since Qwen3.8 shipped. I think it may be damaged more than 3.6 at similar levels of quantization?

If hyperscalers hadn't bought up almost all the fast RAM production for the next several years, 32GB of VRAM would be tolerably cheap—a lot by "home PC" standards, but not terrible by "professional tools" standards. Sadly, the RAM market is amazingly ugly right now.

> I doubt the timing differential here, but even still I run my 3090 pretty heavily with inference workloads and it stays cooler than when I use it for gaming.

Yeah, running inference on a laptop is likely to run quite hot. But in an ATX case with decent cooling, it's generally a lower load than gaming. One handy tip: Many Nvidia GPUs (and some from other manufacturers) support power limits. For example, limit a 5090 to 400W instead of 600W, and it will run much cooler. You might lose 11% off your tokens/sec (depending on the exact card).