# oMLX Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/omlx
> Markdown URL: https://aitinkerers.org/technologies/omlx.md
> Technology record last updated: 2026-06-25T12:59:39Z
> Generated: 2026-09-22T14:37:57Z

oMLX is an open-source, macOS-native inference server that optimizes local LLM workflows on Apple Silicon using a two-tier, paged SSD KV cache.

Built specifically for Apple Silicon, oMLX bypasses unified memory limits by offloading inactive context blocks to your SSD in safetensors format. This two-tier KV cache architecture drops time-to-first-token (TTFT) from 90 seconds to under 5 seconds during long-context agentic workflows (like running Claude Code or Cursor). By combining continuous batching via mlx-lm with a native macOS menu bar app and an OpenAI-compatible API, it delivers up to 3x faster generation speeds on standard hardware without taxing your system's active RAM.

- Official technology site: https://omlx.ai
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Scrape, sense, snipe: local LLMs reading Twitter to trade Polymarket](https://zurich.aitinkerers.org/talks/rsvp_jO-ELvIgcaQ)

A self-hosted pipeline that scrapes Twitter, runs local LLMs to score sentiment, cross-references on-chain Polymarket activity, and surfaces ranked trade suggestions on a dashboard. I review the suggestions and place the trade myself.

- Event context: AI Tinkerers Zürich: July Build Night with Swisscom Ventures — 2026-07-01 — Zürich
- Public talk page: https://zurich.aitinkerers.org/talks/rsvp_jO-ELvIgcaQ

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