"Ollama's new support for Apple's open source MLX framework significantly enhances the performance of large language models on local computers, particularly benefiting users with Apple Silicon chips."
"The introduction of Nvidia's NVFP4 format for model compression allows for much more efficient memory usage, which is crucial for running large models effectively."
"As local models gain popularity, driven by frustrations with high subscription costs for existing tools, developers are increasingly experimenting with running models on their own machines."
Ollama has introduced support for Apple's MLX framework, enhancing the performance of large language models on local computers. The system has improved caching performance and now supports Nvidia's NVFP4 format for better memory efficiency. These advancements are particularly beneficial for Macs with Apple Silicon chips. The rise of local models, driven by frustrations with subscription costs for tools like Claude Code and ChatGPT Codex, has led to increased experimentation among developers. Currently, only the 35-billion-parameter variant of Alibaba's Qwen3.5 model is supported, requiring significant hardware specifications.
Read at Ars Technica
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