What is BaseRT?

BaseRT is a high-performance LLM runtime purpose-built for Apple Silicon. It installs with a single terminal command and lets you run large language models entirely on your own device—no cloud dependency, no API keys, and no data leaving your machine. Designed for speed and local privacy, BaseRT is positioned as the fastest runtime available for Apple’s M-series chips.

Who it's for

• Developers who want to run local coding agents without sending code or context to external servers
• Privacy-conscious engineers who need on-device inference for sensitive workloads and cannot rely on cloud APIs
• AI researchers and tinkerers who benchmark open-source models and need maximum token throughput on Apple hardware

Key features

One-command install

BaseRT is installed with a single curl command: curl -LsSf https://basecompute.co/install.sh | sh. No manual compilation, no dependency wrangling—just a shell pipe and you’re ready to serve models.

Benchmark-leading performance

On decode tasks, BaseRT outperforms MLX by up to 33% and llama.cpp by a similar margin. On prefill tasks, the gap widens dramatically: up to 6.4x faster than llama.cpp and 3.9x faster than MLX, measured on an Apple M5 Pro with models like Qwen3 30B-A3B and Gemma 4 E2B.

Local coding agent integration

BaseRT ships with a plugin that turns your local model into a coding agent. Serve a model with basert serve basecompute/gemma-4-E4B-it, install the plugin, and run pi—everything stays on your machine. No API keys, no data leaving your device.

Broad model support

BaseRT supports a wide range of open-source models including Qwen3, Qwen3.5, Qwen3.6, Llama 3.1, Llama 3.2, Gemma 3, Gemma 4, Mistral, Phi-3, and Nomic BERT. New models are added through the community and official releases.

What stands out

BaseRT is the fastest LLM runtime on Apple Silicon—up to 6.4x faster on prefill than llama.cpp.

That performance edge isn’t just a headline number. For developers running coding agents or interactive applications, faster prefill means lower latency on prompt processing, which directly translates to a snappier user experience. The decode speed improvements also mean higher throughput for streaming responses. Combined with the one-command install and local-only operation, BaseRT offers a rare combination of speed and simplicity that’s hard to find in other runtimes.

Worth checking out if…

You work on Apple Silicon and need the fastest possible local inference—especially for coding agents, privacy-sensitive workloads, or any scenario where you want to keep data on-device without sacrificing performance. If you’ve been using MLX or llama.cpp and want to see if a 15–33% decode boost and up to 6.4x faster prefill makes a difference in your workflow, BaseRT is worth a try.