How are you guys finding the GMKtec EVO-X2 128GB? Any regrets?
Posted by Sea-Championship2939@reddit | LocalLLaMA | View on Reddit | 11 comments
As the title says, I kind of am.
My unit runs pretty hot and just isn’t performing as well as I expected.
I’m trying to run some 70B models and I’m not satisfied at all.
I’m seriously considering returning it and going for a Mac Studio M4 Max 128GB instead.
With the recent updates to Exo and MLX, you can now cluster multiple Macs together and run truly massive models, something the EVO-X2 just can’t compete with.
What do you think? How is your EVO-X2 holding up a few months after purchase?
Also should I just wait for the Mac Studio M5 in June? Apple releases their quarterly earnings report on April 30th, so maybe they’ll announce some release dates then…
StardockEngineer@reddit
These posts have to be AI generated. No one is buying a whole LLM machine and running an old ass model at 70b
MelodicRecognition7@reddit
https://old.reddit.com/r/LocalLLaMA/comments/1s0g8wb/gatekeeping_in_ai/
HopePupal@reddit
100%. always check the post history: this guy's normal posting is the text equivalent of pointing and grunting.
dsartori@reddit
I've had mine for about five months now. It's now my sole inference source for work. Midsized MoEs are the way to go to get good performance out of them. Qwen3.5 and now Qwen3.6 have made it a viable platform for just about everything I do with LLMs.
70b dense models and larger will certainly run poorly on these devices.
Kulqieqi@reddit
There's GMKtec EVO-X2 with 64gb for half the price, guess it's better deal than 128gb for horsepower 395 has.
dsartori@reddit
I would not go the 64GB route, especially running Windows. 96GB is as low as I would go if you want to target small MoEs only (27-35B). 128GB is worth the purchase if you have the resources as it allows you to access the midsized class of MoE models (100-130B).
Qwen3.5-122B was my daily driver until 3.6-35B came along with comparable output quality and much faster prompt processing.
sittingmongoose@reddit
FYI qwen 3.6 27b dense just came out and supposedly smokes 35b. Just released like an hour ago.
dsartori@reddit
I see that. I’ll likely wait for the midsized MoE just because they perform so much better on Strix hardware.
CryptographerKlutzy7@reddit
No regrets at all.... I've been using it to train small models, and be my daily coding box, AND do gaming. No regrets at all. Just don't try to decode video at the same time as anything else.
DataGOGO@reddit
Nothing stopping you from running two+ EVO's in a cluster, but just like with the mac's, the interconnection is so slow it defeats the purpose.
Look_0ver_There@reddit
I have two of them. If you run 70B dense models then you're going to have a very bad time. Heck, even 27B or 31B dense models are pretty slow. The machines just don't have the memory bandwidth required to run those at speed.
These machines run best with MoE models. MoE models have gotten so good now that I'm sort of puzzled as to why people insist on taking a "70B dense or nothing!" attitude.
Run a Q5_K_M quant of Qwen3.5-122B-A10B, or an IQ3_XXS quant of MiniMax-M2.7 if you want to see about the best that these machines can do in terms of model intelligence and not be horribly slow at it.
In short, your problem is your model selection. Something something "horses for courses" and all that.