Rapid-MLX
The 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. (by raullenchai)
karateclub
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020) (by benedekrozemberczki)
| Rapid-MLX | karateclub | |
|---|---|---|
| 6 | 1 | |
| 2,756 | 2,275 | |
| 90.1% | 0.0% | |
| 9.8 | 6.7 | |
| 4 days ago | almost 2 years ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Rapid-MLX
Posts with mentions or reviews of Rapid-MLX.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2026-05-05.
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Chrome's Gemini Nano Prompt API: A Step-by-Step Guide
💡 💡 Make the fallback cheap to operate. The whole point of using Nano on the supported path is reduced cost. If your fallback is GPT-5.5 at $5/M tokens, you've moved the bill, not deleted it. Two patterns work well: (1) route the fallback to a smaller hosted model (Haiku, Gemini Flash, Mistral Small) that matches Nano's "short summarization" sweet spot; (2) for Mac users specifically, run Rapid-MLX as your /api/llm endpoint — Apple Silicon owners get on-device performance via your server's Mac, not theirs. Same thesis as our DeepClaude guide: the harness is one product, the model is another, and you can swap them.
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Anthropic is allowing the Claude CLI to run OpenClaw again
> Large-context requests auto-route to a cloud LLM (GPT-5, Claude, etc.) when local prefill would be slow. Routing based on new tokens after cache hit. --cloud-model openai/gpt-5 --cloud-threshold 20000
https://github.com/raullenchai/Rapid-MLX
- Show HN: Rapid-MLX – Run local LLMs on Mac, 2-3x faster than alternatives
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Gemma 4 on Apple Silicon: 85 tok/s with a pip install
I've verified this end-to-end with structured output (output_type=BaseModel), streaming, multi-turn conversations, and multi-tool workflows. Test suite here.
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vLLM-mlx – 65 tok/s LLM inference on Mac with tool calling and prompt caching
pip install git+https://github.com/raullenchai/vllm-mlx.git
karateclub
Posts with mentions or reviews of karateclub.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Embedding attributed graphs
Check out Karate Club (https://github.com/benedekrozemberczki/karateclub) . It has implementations for many attributed node embedding algorithms.
What are some alternatives?
When comparing Rapid-MLX and karateclub you can also consider the following projects:
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
PDN - The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
MindsDB - General-purpose AI designed for knowledge workers — creators, strategists, and operators — and individuals seeking AI systems they can truly control to help them get work done, with full flexibility to extend and deploy anywhere (VPC, on-prem, or cloud).
openskill.py - Multiplayer Rating System. No Friction.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
tensorflow - An Open Source Machine Learning Framework for Everyone