Also developers often want more ram, and if youre on the mac side, the M series ram works as video ram for loading and running models, so there’s a good chance you can already run something better than is typical of others, and apple is focusing on this by adding more NPUs and increasing memory bandwidth. They arent good at training, but can do inference.
I have a model with 64GB of ram. I’ve limited context to 16k, in an effort to make it more stable, but tbh - it is rather unreliable no matter what I do. With my setup - mlx_lm and webui, it frequently collapses or loops, no matter the settings. I have done a lot of debugging and have concluded it is probably inherent model behavior.
That’s lame about the looping, but ya I don’t think that’s a mlx issue, I’ve had it on my desktop with my nvidia card as well. I also tried fussing with configurations, and I was never sure if it was the models or my settings. I was mainly toying around with LLama based models.
There is a significant overlap between developers and gamers.
Most developers use their work provided machines, which aren’t gaming machines with giant GPUs because again, GPUs don’t help development at all.
Also developers often want more ram, and if youre on the mac side, the M series ram works as video ram for loading and running models, so there’s a good chance you can already run something better than is typical of others, and apple is focusing on this by adding more NPUs and increasing memory bandwidth. They arent good at training, but can do inference.
I’m on a MacBook with M2, 32GB ram. Literally just tried:
Well, I guess I’ll try again next year.
For context: my home pc is running gemma4:31b just fine. It’s also a beefy ass desktop, though.
Are you running an mlx model? If not, try that. My m4 macbook runs qwen3.6-35b-a3b lightning fast. Has its issues, but fast nonetheless.
What kind of context length can you get with that, and how much ram?
I have a model with 64GB of ram. I’ve limited context to 16k, in an effort to make it more stable, but tbh - it is rather unreliable no matter what I do. With my setup - mlx_lm and webui, it frequently collapses or loops, no matter the settings. I have done a lot of debugging and have concluded it is probably inherent model behavior.
That’s lame about the looping, but ya I don’t think that’s a mlx issue, I’ve had it on my desktop with my nvidia card as well. I also tried fussing with configurations, and I was never sure if it was the models or my settings. I was mainly toying around with LLama based models.
You might be doing something wrong, models that size shouldn’t be that slow if properly configured on a 32gb m2
You need a metal optimized client and model, not the same models you’d run on your desktop machine.