ycui7

it is not about simple or complex circuit. non-linear process creates complicate behavior. a nonlinear process can be very simple, and the output can be very complicated.

too bad, no one write code anymore. a nice trick sadly become irrelevant .

like 99% of all prototype fit 1oz copper and within 4 layers. no via-in-pad.

rids proto fully booked. so they have no o capacity. we cannot even get a quote to know the pricing of grids proto.

does this cause blockage in the canal ?

this is not right. vllm can easily load safetensors model at >5GB/s if not faster when setup right. did you make the compile cache persist? if you use docker, you should bind mount the kernel compile cache, so they don't need to be recompiled each time vllm restart.

you do can change font size in settings, but not with keyboard shortcut. for some reason, they decided to limit font size to 17 max.

click the link, or read the PDF.

all authors are listed. there is no conspiracy to hide authorship.

arxiv simply want to keep the page short not too long.

remind me in the old time, we use cc to compile code to machine code. it was cc not gcc.

llm is not a deterministic program. the same model won't even return deterministic answer. what's the point keep the model freezed?

if you want deterministic returns, you should set the temperature to 0 to get the best possibility of deterministic.

the fact that this author cannot get qwen3.8-27b run at the same speed as qwen3.6-27b, says the article is not worth reading. the author does not know anything about how to run local AI. 3.8 and 3.6 are the same model with different weight.

both tg and pp speed are so terrible on author's machine.

because it has 1T ssd not 4T

Cerebras is an uncut whole wafer. Each wafer gets you 44GB SRAM (not a typo, SRAM, not DRAM/VRAM). A few years ago, leading process node wafer from tsmc is $20K/ea without guarantee on yield.

A single full wafer likely can run qwen3.6-27b alone. But won't be enough to run bigger models, which are pretty much all popular models.

if you have the VRAM, use offical release. quantized model lose focus after long context and can do damages or thinking loop

that is why we enable web search for the agent. the memory can come from the internet.

deepseek-v4-flash needs web search to return true facts.