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Running local models on Macs gets faster with Ollama's MLX support: why this signal is getting harder to ignore

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.

Emerging The topic has initial corroboration, but the newsroom is still waiting on stronger confirmation.
Reference image for: Running local models on Macs gets faster with Ollama's MLX support: why this signal is getting harder to ignore
Reference image from Ars Technica. Ars Technica

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.

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What happened

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.

Why it matters

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. The key angle is that AI is moving closer to everyday use instead of staying in demo mode.

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What to watch next

The next thing to watch is whether the change moves quickly into real product use. Patrick Tech Media is cross-checking the thread against Ars Technica.

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