Rapid MLX

Rapid-MLX

Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents.

Up to 4× faster than Apple's MLX (mlx-lm), 1.5× on a typical task — same model, same weights.

Decode speed, Qwen3.5-9B 4-bit on a Mac mini M4 Pro, greedy decoding, both servers at their defaults — per-task results, method, and raw data.

Faster decode than oMLX and LM Studio on Qwen3.5-9B, Qwen3.8-27B, and Qwen3.6-35B

Measured speed on a Mac Studio M5 Max (36 GB) — Rapid-MLX 0.16.1 vs oMLX 0.7.0 and LM Studio, using the same base 4-bit weights for each model.

Model	Metric	Rapid-MLX	oMLX	LM Studio
Qwen3.5-9B	Decode (tok/s)	115.5	77.9	81.0
Qwen3.5-9B	4 streams (tok/s)	248.2	224.6	230.0
Qwen3.8-27B	Decode (tok/s)	37.9	25.3	26.0
Qwen3.8-27B	4 streams (tok/s)	82.8	75.3	69.7
Qwen3.6-35B	Decode (tok/s)	173.4	145.8	124.5
Qwen3.6-35B	4 streams (tok/s)	293.9	281.9	265.6
Qwen3.6-35B	2K-prompt first token (s, lower is better)	0.55	1.14	1.49

Single run per engine; default serving modes with Rapid's MTP text mode, oMLX's SSD cache, and LM Studio's configured context and four parallel slots. Full results and raw data.

<b>rapidmlx.com</b> ·
Docs ·
Model mirror ·
Desktop app ·
Discord

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How it compares

Feature facts only, taken mostly from each project's own documentation as of 2026-09-26 (sources below). For speed, see the measured results above.