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BaseRT

6.4x faster than llama.cpp on Apple Silicon — local LLM inference, zero token cost.

Dev ToolsOpen Source

BaseRT is the fastest LLM runtime on Apple Silicon. Install it with one command and run local models on your own device — no per-token cost, full privacy. 6.4x faster than llama.cpp, 3.9x faster than MLX. Supports multiple models and is optimized for always-on background agents.

What is BaseRT?

BaseRT is the fastest LLM runtime on Apple Silicon, offering 6.4x performance over llama.cpp and 3.9x over MLX. It enables local LLM inference with zero per-token cost and full privacy, installable via a single command.

Key features

  • 6.4x faster than llama.cpp on M-series Macs
  • 3.9x faster than Apple MLX framework
  • Single-command installation
  • No per-token cost — run models locally
  • Full data privacy — no data leaves your device
  • Supports multiple model formats
  • Optimized for always-on background agents
  • Open source

Who it's for

  • Developers running local LLMs on Apple Silicon for development
  • Always-on AI agents that need low-cost continuous inference
  • Privacy-sensitive workloads requiring on-device processing
  • Building local AI-powered applications without API dependencies
  • Testing and benchmarking different open models locally

When not to use it

Not ideal if you need GPU-level performance on non-Apple hardware, or require cloud-scale throughput. BaseRT is optimized specifically for Apple Silicon — cross-platform use cases should consider alternatives like vLLM or TGI.

FAQ

What models does BaseRT support?

BaseRT supports popular open weight models compatible with Apple Silicon's unified memory architecture. Check the docs for the full compatibility list.

Is BaseRT free to use?

Yes, BaseRT is open source and free. No token costs or subscription fees.

How does it compare to Ollama?

BaseRT claims 6.4x speed over llama.cpp. Ollama is easier to get started with but BaseRT targets raw performance on Apple Silicon.

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Submitted by Lukas WesemannXLaunched July 21, 2026

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