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)
redframes
General Purpose Data Manipulation Library (by maxhumber)
| Rapid-MLX | redframes | |
|---|---|---|
| 6 | 12 | |
| 2,756 | 326 | |
| 90.1% | 0.6% | |
| 9.8 | 1.4 | |
| 4 days ago | about 3 years ago | |
| Python | Python | |
| Apache License 2.0 | BSD 2-clause "Simplified" License |
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
redframes
Posts with mentions or reviews of redframes.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2025-04-10.
- Redframes
- Big Book of R
- What is something you wish there was a Python module for?
- Redframes: General Purpose Data Manipulation Library
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Modern Polars: an extensive side-by-side comparison of Polars and Pandas
I'm not GP, but I find the pandas API incredibly inconsistent and difficult to remember how to do simple transformations. For example, it sometimes overloads operators because it doesn't use built in language features like lambdas. There are reasons for the inconsistency, but using the alternatives like R's tidyverse or Julia's DataFramess.jl is like night and day for me.
I found RedFrames [1] recently which wraps Pandas dataframes with a more consistent interface, it's probably what I'd use if I had to write data transformations that had to be compatible with Pandas.
[1] https://github.com/maxhumber/redframes
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Ask HN: How you maintain your daily log?
[2022-10-23 14:11:15]: Question []: should we use Red Frames (https://github.com/maxhumber/redframes) in addition to Pandas? Criteria for decision? @me #projectLion
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Python 3.11.0 final is now available
If you like writing chain-able pandas, you should check out: https://github.com/maxhumber/redframes
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Add your own custom methods to third-party types with this pattern
I intend to use this pattern in my redframes library to hijack some pd.DataFrame methods.
- GitHub - maxhumber/redframes: [re]ctangular[d]ata[frames]
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Ask HN: What are you doing this weekend?
I'm dog-fooding my new Python data manipulation library, redframes: https://github.com/maxhumber/redframes
To help me prep for my Fantasy Hockey Draft next week!
What are some alternatives?
When comparing Rapid-MLX and redframes you can also consider the following projects:
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
tensorflow - An Open Source Machine Learning Framework for Everyone
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).
pydeep - Deep learning in Python
gym - A toolkit for developing and comparing reinforcement learning algorithms.
Keras - Deep Learning for humans