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oMLX manages each model's lifecycle with four pieces: a downloader that pulls weights from Hugging Face, aliases that rename the model in the API, a TTL that unloads it after idle time, and a tiered KV cache that spills blocks to SSD when RAM fills up.
oMLX MCP is a bridge that exposes your local oMLX server as Model Context Protocol tools. The mcp_omlx package connects Claude Desktop to the models running on your Mac and gives you seven tools to list models, load and unload them from memory, and run inference without leaving the client.
Tested May 2026 recipe: oMLX 0.3.8 on Mac M5 Max with 128 GB, TurboQuant at 3.5-bit, Qwen 3.6 35B-A3B model stack, Claude Code wiring and real benchmarks.
100 must-have apps for your M5 Mac organised into 20 categories: browser, notes, terminal, IDE, containers, AI and more. Each pick with purpose, key features, plugins, pricing in EUR and the official link.
Installing Ollama on an Apple Silicon Mac is as simple as running one Homebrew command. Then pick a model based on available RAM (Phi-3 for 8 GB, Llama 3.1 8B for 16 GB) and expose the local, OpenAI-compatible HTTP API on port 11434 to plug it into your own applications.
