Those in the 1000+ prefill and 100+ decode range on Qwen3.6 35B at Q4, what hardware are you running?

Trying to see what I can scrounge together bare minimum hardware requirements to get up to that rough speed.

Right now I'm running an RX6600XT and Ryzen 7 5700X with 32GB of DDR4 at 3600MHZ. CachyOS, vanilla llama.cpp built with ROCm and a workaround going to make it work with my GPU. Works about 30-35% faster on prefill vs vulkan, no difference on decode. I've been fighting with llama.cpp settings for a while and this is about the fastest I've gotten. Manually setting gpu layers or experts in system memory, basically anything that manipulates where the model goes, has always resulted in a regression on my system. Settings have been focused on both token efficiency (i've never seen so few reasoning tokens for the more complex tasks I ask of it, like sometimes sub 1k for a research task, sub 10 for a hello vs the classic 3000 token "how do I respond to 'hi'" trap you see), and actual inference speed.

With that setup, I currently get between 270 and 300 t/s prefill and \~30t/s decode. This is the best I've managed. Model in particular is Qwen3.6 35B A3B, Unsloth Q4\_K\_XL. It's the only model I've tested that can consistently perform in my harness while also running at a speed that is functional for the current focus of the project, being the text interfaces and mobile app. Except the part of my project I really wanted to focus on is voice interaction, and this isn't there yet. It's not far off, but 3-4X faster inference and prefill will actually make it near alexa speed for smart home actions, and almost actually interactive for heavier home management/shop assistant stuff that it was originally designed to be.

Online benchmarks for hardware are simply useless. I look at sites like canirunai or willitrunai and look at *my* hardware on those sites, only to find them stating the same model runs 10x worse than I actually get, so I know I can't trust their numbers.

So I ask those of you with more compute than I: What are you running hardware wise to get to those numbers in the title or higher?