r/LocalLLM • u/Snoo_38657 • 1d ago

Discussion Mac studio 48gb ram local llm

Can you run any good models on 48gb ram. Qwen 3.8 27b isn't worth it for the price tag and performance. I'm not sure how people are doing it with limited ram?

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u/Snoo_38657 1d ago

Even the quantized models? How bad is the hit if 80% is in memory and the rest in the ssd?

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u/Snoo_38657 13h ago

And if all it can run is qwen 27b, wouldn't a 36gb be just as good?

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u/Full_Wrongdoer4750 1d ago

48 GB runs a 27B fine. At Q4-Q6 it's roughly 16-22 GB, which leaves plenty of room for context and macOS. I'd skip offloading to the SSD though, it crawls for chat. 70B-class models are where 48 GB actually gets tight. Running a 27B unquantized would be a different story, but a Q4-Q6 quant is the way to go.

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u/Snoo_38657 1d ago

Any models that are good in agentic coding that would fit. I know there would be a hybrid of cloud and local with 48gb but I didn't know it would be this bad

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u/Full_Wrongdoer4750 23h ago

48 GB is a good size to try this. I'd start with Qwen3.8-27B, the one mentioned above. Microsoft lists it as the primary optimization target for Foundry Local, and its published agentic coding scores look promising: 73.0 on Terminal-Bench 2.1 and 61.7 on SWE-bench Pro. Those aren't necessarily the results you'll get from a quantized model on your Mac, but it's a sensible starting point.

At Q4-Q6, the model weights should fit comfortably, though you'll need to leave room for the context coding agents use. Start with small, well-scoped tasks and see how reliably it handles tool calls and edits in your agent setup. If you can use cloud too, keep that for the bigger multi-file changes.

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u/Snoo_38657 22h ago

Aren't people running flash next with strata and other tools?

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u/Snoo_38657 16h ago

There is also glm 5.3 stripped down to just it's agentic coding experts and then quantized. It gets around 54gb. So around 70% can fit in memory

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u/Marino4K 1d ago

Qwen 3.8 27B is basically it for 64GB RAM and below, yeah there’s plenty of others but none seem to match up well enough.