Okay, so I've seen a few older threads on this but figured with Qwen3.8 and the newer inference engines it's worth an ask. I'm looking to buy a new Macbook Pro. At the least, I'm looking at the 64GB M5 Max with the higher-spec GPU. I'm having a hard time justifying spending $2000 more for an incremental 64GB of RAM (for net a total of 128GB). What's the state of inference on Apple Silicon? For model availability, are MLX quants typically served up as fast and with as much selection as general GGUFs? Does MLX make that much of a difference? For those of you with a Mac (or unified RAM system in general), what can you do with 128GB that you can't with 64GB? As a frame of reference, my desktop has a 5090 FE and 128GB of System RAM. While Qwen3.8 Flash Next with Strata is great, there's still a significant trade-off between the amount of lobotomy, usable context size, and prefill/ decode speed. Same goes for 27B, the moment I run exceed VRAM performance plummets. I end up using a more conservative deployment (more aggressive quant, lower context size) than I technically could fit in VRAM simply because I often end up 1 browser tab away from system RAM spillover. If my desktop had 64GB of VRAM, I think I'd be satisfied? But it's hard to say because I'm used to Windows/ everything else running in system RAM anyway. No idea what to expect with a unified RAM machine. Would love to hear your thoughts and usage experiences! Is Qwen3.8 Flash Next actually usable on 128GB? Is the $2K premium justified for "future proofing"? Also toying with the idea of a Klarna lease so that I don't have to fully commit right now, but feels wasteful especially since I'd trade-in my M2 Max (32GB) which would shave ~$1500 off the sticker price of a new machine. Thanks 🙏   submitted by   /u/ComputerSiens [link]   [comments]