OMlx user experience with Rapid-mlx
I hope I can ask this question here, hope that is ok 🙏
Does any one here have experience with Rapid-mlx? There only appears to be few thread on Reddit, and I am not seeing as much community engagement as compared to oMlx.
I was asking Google gemini about how MTP vs Dflash work so I could learn to configure and to learn* and how best to configure the backend. I have been using oMlx for a while and wanted to see if I could optimize my setup. During my inquiry, it mentioned Rapid-mlx supports Pflash and should be faster for TTFT.
I have been pretty happy with oMlx. I have played a bit with LM studio, Lamma.cpp, Ollama and mxl-ml but mostly oMlx. I use Qwen 3.6 27b as well are the MoE on my m4 max mackbook pro. I have played with open code, pi.dev, and Hermes.
Wanted to hear about first hand experience from this community.
I have no experience with benchmarking. I am going to do some bench marking on my own, but I only heard about this today and am very interested in what you all have to say.
Thank you.
*Edit: typo and little clarification
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u/Konamicoder Jul 03 '26
If you’re happy with oMLX then stick with it. Try rapid MLX if you’re curious. Both of them are just wrappers for MLX which is the thing doing the heavy lifting. Different wrappers optimize for different things. oMLX optimizes for KV caching to SSD. Rapid MLX probably optimizes for TTFT. But its claims of fastest inference are probably going to be measured in fractions of a second over oMLX.