Nope. For 27B a 16GB video card (8 in a pinch) + 16 (32 better) GB RAM will work for reasonable context, if not screamingly fast. Any M series Macbook with 32 Gb+ (24 in a pinch). Hell, there are setups to run even larger models of a nvme drive if you have enough patience.
Smaller models like 8B are fine on a CPU, or even a phone.
I mean, if you’re really patient you can even run with CPU only as long as you have enough RAM… My ~decade old computer with DDR3 RAM gets 14 tok/s prompt processing and ~5 tok/s decode on MoE models (e.g. a Qwen 3.6 35B-A3B variant at Q6_K – my current default model). That pp tok/s is painfully slow… but it still works!
Same computer, same model but using a discrete GPU that can fit all the weights on the card – ~900 tok/s prompt processing, ~70 tok/s decode.
qwen 3.6 27b runs on an AMD AI MAX 395+ fairly well.
I have one in a laptop with 64gb of ram that I bought before things went too crazy for $2200. Not sure how much one is now.
Anyway, you don’t need a datacenter and that’s why I personally think the current AI “boom” is a bubble around a nascent tech that’s not really ready for lots of the situations it’s been sold for. 🤷♂️
I haven’t really found that to be the case for my uses, but getting much faster decode is really useful for me… Have you tried running the MoE model at a higher quant? I usually use Q6_K.
I run both of them at Q8, unquantized KV cache and same settings.
35b does really well at most tasks but once the dependencies get complicated and the tool calls reach into the hundreds, 35b struggles where 27b still excels.
So generally I use 27b unless I need it fast, then I swap to 35b or 122b depending on what I need.
I have been running Qwen 3.6 for a while now on a Mac Mini and it’s been really nice. It is responding to changes requested in a code review right now and it’s doing a pretty good job of it.
How much does it even cost to run that stuff? Do you need your own private data center?
Nope. For 27B a 16GB video card (8 in a pinch) + 16 (32 better) GB RAM will work for reasonable context, if not screamingly fast. Any M series Macbook with 32 Gb+ (24 in a pinch). Hell, there are setups to run even larger models of a nvme drive if you have enough patience.
Smaller models like 8B are fine on a CPU, or even a phone.
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I don’t think you can run 27B on 16GB without degrading its quality. You’d have to drop to lower quantization. Is there some new magic?
35B A3B runs well on 8 and 16GB GPUs.
Everything runs well if one is patient enough 😂
But yeah, with a smaller context and carefully offloading some of the layers to the CPU, it’ll run just not very fast. And definitely using Q4 quants.
I mean, if you’re really patient you can even run with CPU only as long as you have enough RAM… My ~decade old computer with DDR3 RAM gets 14 tok/s prompt processing and ~5 tok/s decode on MoE models (e.g. a Qwen 3.6 35B-A3B variant at Q6_K – my current default model). That pp tok/s is painfully slow… but it still works!
Same computer, same model but using a discrete GPU that can fit all the weights on the card – ~900 tok/s prompt processing, ~70 tok/s decode.
Yeah, down to 4bit, which works OK, but 35BA3B is much more performant. Sometimes you want the monolithic quality and damn the speed…
IQ3s perform very well these days.
qwen 3.6 27b runs on an AMD AI MAX 395+ fairly well.
I have one in a laptop with 64gb of ram that I bought before things went too crazy for $2200. Not sure how much one is now.
Anyway, you don’t need a datacenter and that’s why I personally think the current AI “boom” is a bubble around a nascent tech that’s not really ready for lots of the situations it’s been sold for. 🤷♂️
Try Qwen 3.6 35B-A3B on your hardware instead; it’s much faster.
27b is much better though…
And it still gets 15-20 t/s with MTP which is plenty fast.
I haven’t really found that to be the case for my uses, but getting much faster decode is really useful for me… Have you tried running the MoE model at a higher quant? I usually use Q6_K.
I run both of them at Q8, unquantized KV cache and same settings.
35b does really well at most tasks but once the dependencies get complicated and the tool calls reach into the hundreds, 35b struggles where 27b still excels.
So generally I use 27b unless I need it fast, then I swap to 35b or 122b depending on what I need.
I’ll check it out!
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A 3090 works great. Any 24-32 GPU would work well.
I have been running Qwen 3.6 for a while now on a Mac Mini and it’s been really nice. It is responding to changes requested in a code review right now and it’s doing a pretty good job of it.
No you don’t need a data center, this can run on any current gaming PC with a GPU that has 16GB+ VRAM.
Although to get good token generation speed and full context you need at least 24GB VRAM.