LLMs
Running local models on Macs gets faster with Ollama’s MLX support
Apple Silicon Macs get a performance boost thanks to better unified memory usage.
Samuel Axon
–
Mar 31, 2026 7:00 pm
|
54...
## 正文
LLMs
Running local models on Macs gets faster with Ollama’s MLX support
Apple Silicon Macs get a performance boost thanks to better unified memory usage.
Samuel Axon
–
Mar 31, 2026 7:00 pm
|
54
A graphic made by Ollama to announce MLX support.
Credit:
Ollama
A graphic made by Ollama to announce MLX support.
Credit:
Ollama
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Ollama, a runtime system for operating large language models on a local computer, has introduced support for Apple’s open source
MLX
framework for machine learning. Additionally, Ollama says it has improved caching performance and now supports Nvidia’s
NVFP4
format for model compression, making for much more efficient memory usage in certain models.
Combined, these developments promise significantly improved performance on Macs with Apple Silicon chips (M1 or later)—and the timing couldn’t be better, as local models are starting to gain steam in ways they haven’t before outside researcher and hobbyist communities.
The recent runaway success of OpenClaw—which raced its way to over 300,000 stars
on GitHub
, made headlines with experiments like
Moltbook
and became an obsession in
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