The era of powerful, private AI on your Mac has officially arrived! A recent breakthrough combining Ollama with Apple’s MLX framework is delivering astonishing performance with leading Chinese large language models, bringing cloud-level AI capabilities directly to your desktop.
Ollama & MLX: A Synergistic Partnership
For months, the local AI community has been eagerly anticipating tighter integration between popular tools and Apple’s silicon. Now, that wait is over. Ollama, the incredibly user-friendly framework for running large language models locally, has received a significant update – full integration with Apple’s MLX machine learning framework. This isn’t just a minor tweak; it’s a fundamental shift that unlocks the true potential of Apple’s M-series chips (M1, M2, M3 and now M4) for AI workloads.
Previously, running demanding models like Qwen 3.5 on a Mac required compromises. Now, thanks to MLX’s optimized execution on Apple silicon, those compromises are largely a thing of the past. The results are genuinely impressive. According to reports from @hank_aibtc, testing with the Alibaba Qwen3.5-35B model shows prefill speeds reaching a blistering 1851 tokens/s and decoding speeds of 134 tokens/s. These figures are comparable to, and in some cases exceed, performance experienced with cloud-based APIs – all without the latency or privacy concerns.
Qwen 3.5 on Mac: A Game Changer
The choice of Qwen 3.5 is particularly noteworthy. Developed by Alibaba, Qwen is a powerful open-source large language model that has been rapidly gaining traction. Its availability on Mac, running efficiently through Ollama and MLX, represents a significant step forward for accessibility to cutting-edge Chinese AI technology. The integration also supports NVFP4 quantization, meaning the model can run with a relatively small memory footprint. This is crucial for users who don’t have the latest and greatest Mac with massive RAM configurations. In fact, a Mac with 32GB of RAM is now sufficient to comfortably run Qwen 3.5, opening up local AI experimentation to a much wider audience.
Beyond Chatbots: Multi-Agent Potential
The implications extend far beyond simply having a faster chatbot. The performance boost makes complex multi-agent tasks – like using Claude Code or other AI-powered tools for coding assistance, content creation, or data analysis – genuinely viable on a Mac. The ability to run these models locally also addresses critical privacy concerns. Your data stays on your machine, and you’re not reliant on an internet connection. This is a huge win for developers, researchers, and anyone who values data security. As someone who’s spent years observing the tech landscapes of both Silicon Valley and Shenzhen, I can attest to the growing emphasis on privacy-preserving AI, and this development aligns perfectly with that trend. It’s a clear demonstration of Chinese AI models making inroads on consumer-grade hardware, a feat previously dominated by Western tech giants.
Key Takeaways
- Performance Leap: Ollama + MLX delivers cloud-like AI performance on Apple Silicon.
- Accessibility: Qwen 3.5 is now readily accessible to Mac users, even with 32GB of RAM.
- Privacy & Security: Local execution ensures data remains on your device, enhancing privacy.
- Developer Productivity: Faster speeds unlock new possibilities for AI-powered development workflows.
This is a pivotal moment for local AI on the Mac, and a testament to the power of open-source collaboration and innovative frameworks. Have you tried running Qwen locally on your Mac yet? Share your experiences!
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📷 素材來源：@hank_aibtc
📌 相關標籤：Local AI、Apple Silicon、Qwen、Ollama、MLX、AI Models、Mac、Privacy
✏️ 中國科技 from grok (英) | 更新日期：2026/04/03
