Getting models to load in LM Studio [64GB Mac]

Posted by PracticlySpeaking@reddit | LocalLLaMA | View on Reddit | 11 comments

How to troubleshoot this? ... I have a 64GB Mac, and LM Studio Hardware info reports 48GB VRAM. But after grabbing a bunch of models\* with \~32 - 48GB file size, most of them will not load (with the "insufficient system resources" message). Am I being naïve thinking these should work in 48GB? Even after using the manual guardrail setting at 48GB and context=4096 there is no joy for anything over \~30GB. Also, I have tried the terminal command (with iogpu.wired\_limit) to increase the fraction of GPU RAM. Should the new limit show up in LM Studio? Or is it brain-dead and just reporting 75% of physical RAM Finally... Is there a best (or better) place to ask n00b questions like this? There is not much going on over on r/LMStudio\-Lounge. Thanks! \*for example, mlx-community/Llama-3.3-70B-Instruct-4bit (39.7GB fs / 36.9GB in loader) mlx-community/Llama-3.3-70b-instruct-dwq MLX (39.7GB / 36.9GB in loader) mlx-community/c4ai-command-a-03-2025-3bit (48.3GB fx / 45.3GB in loader)

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East-Cauliflower-150@reddit

I have used macs extensively for this and you can run up to 56-60gb total (model + context). Just allocate for example 61440mb to gpu (I have even allocated full 128gb on my MacBook Pro without issues and ran qwen3 235b where model alone is ~100gb. First step is to take all guardrails off in lm studio. I have had no issues.

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PracticlySpeaking@reddit (OP)

thanks — turning off guardrails was the biggest step to relieve my disappointment. It doesn't seem to have very good error reporting. I still see failures where the progress bar suddenly skips to 100% (zing!) then start getting "Failed to send message to the model" messages.

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jarec707@reddit

I too have a 64 gb Mac and use LMStudio and have experienced the problem you're having. AFAIK LMStudio doesn't pay attention to how much VRAM you've allocated. If you run really big models in the amount of memory you have you won't have much room for context (like the 70b q4 you mentioned). I recall running some 70b quants but only 2 bit quant. Right now I'm running oss-120b 03ks from unsloth with a small context window and it's surprisingly fast. Unsloth models seem to use memory more effectively, with their smaller quants being surprisingly good. Note that I had to turn off the LM Studio guardrails entirely to run the model and system instability happens. I've got nothing else going on the Mac and have reserved 58gb VRAM (using the Mac as a LLM server). People also like GLM 4.5 Air; the 3b MLX quant is capable for a low quant model. For this, too, I had to disable the LM Studio guard rails. Pro tip: Unsloth models are great; MLX models give a bit more speed. Hope this helps, mate.

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PracticlySpeaking@reddit (OP)

Very helpful, thanks. With guardrails off (and asitop running in terminal) I got the unsloth gpt-oss 120b going. Memory pressure goes yellow when prompting it, and Activity Monitor is showing \~1-1.5GB of swap. 16 tok/sec is not bad, but oss thinks a lot (just trying it out with some basic riddle-type prompts). I increased the VRAM split and used the manual guardrail at 56GB to get Llama 3.3-70b-instruct going. It's not as smart as gpt-oss — couldn't figure out the one with Stone, Often, Canine, ... Freight. The DWQ runs very smoothly, though. This has made my 128GB envy grow!

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jarec707@reddit

Well done! I too have considered 128 gig Mac, but as a practical matter the models I can run on my 64 gig are good enough for my hobbiest uses. I did indeed tweak the GPU offload on the 120 model. You might be able to reserve 58 gigs for VRAM and still have the Mac work if you are not running other programs.

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PracticlySpeaking@reddit (OP)

Yah – and the 128GB are going for a big premium, presumably for people willing to spend more to run large models. The gpt-oss model is odd, having a GPU Offload setting. Usually it defaults to 21/36, and it appears to use both CPU+GPU. Whenever I tweak it the model appears to load but does not work.

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jarec707@reddit

I may have misremembered about tweaking gpu offload…

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SubstantialSock8002@reddit

I think I had to turn off the guardrail entirely for models that approached my max memory. It seems to be too sensitive

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PracticlySpeaking@reddit (OP)

That was the trick - thanks.

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sourpatchgrownadults@reddit

This might work. Although of course, monitor temps closely when pushing the system. Leave some memory headroom too maybe 10-20%. I almost fried my laptop by pushing my vram to near 100%. I think it spiked over 100% and pushed into swap space, and system I/O got overwhelmed. Laptop froze and wouldn't boot anymore. Black screen of death. Lots of hard resets. Couldn't even get into BIOS. This is after letting it cool down too. I eventually got it running again but was a PITA with lots of Google searches troubleshooting to get working again lol.

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PracticlySpeaking@reddit (OP)

That sounds like a Windows / Intel laptop? I am using a Mac.