BaseRT
6.4x faster than llama.cpp, 3.9x faster than MLX
BaseRT launched on July 19, 2026 with 222 votes, #141 of 24,623 launches that month and more than 99% of that year's launches.
What it does
BaseRT is the fastest LLM runtime on Apple Silicon. Install it with one command and run local models on your own device.
On Prefill, up to 6.4x vs llama.cpp and 3.9x vs MLX. Up to 1.33x on Decode. Serve a model with BaseRT, point your agent at it, and keep everything on your machine. No API keys, no data leaving your device. For engineers building on-device AI and working with open sourcefrom basecompute.co
Does a similar job
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Speeding up LLM inference 2x times (possibly)2024 · asciinema.org · ▲419Here's a project I've been working on for the last few months. It's a new (I think) algorithm, that allows to adjust smoothly - and in real time - how many calculations you'd like to do during inference of an LLM model. It seems that it's possible to do just 20-25% of weight multiplications instead of all of them, and still get good inference results. I implemented it to run on M1/M2/M3 GPU. The mmul approximation itself can be pushed to run 2x fast before the quality of output collapses. The inference speed is just a bit faster than Llama.cpp's, because the rest of implementation…

We made our own inference engine for Apple Silicon2025 · github.com · ▲186We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.

Rapid-MLX – Run local LLMs on Mac, 2-3x faster than alternativesApr 2026 · github.com · ▲9The fastest local AI engine for Apple Silicon. 4.2x faster than Ollama, 0.08s cached TTFT, 100% tool calling. 17 tool parsers, prompt cache, reasoning separation, cloud routing. Drop-in OpenAI replacement. Works with Claude Code, Cursor, Aider. - raullenchai/Rapid-MLX

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