Stockyard
Open source LLM proxy. One binary. Zero deps. 40+ providers.
What it does
Every LLM app needs the same six things: proxy routing, cost tracking, caching, observability, audit trails, and safety filters. That's 6+ separate tools, each with its own database and Docker setup. Stockyard replaces all of them with one Go binary. 66 middleware modules. 16 LLM providers (OpenAI, Anthropic, Gemini, Groq, Ollama, and more). Embedded SQLite — no Redis, no Postgres. Install in 30 seconds, dashboard included. MIT licensed. Self-hosted is free forever with no limits.
Does the same job
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, March 2026
the whole month →
Switch from ChatGPT to Claude with import memory feature
AI · Mar 2026 · claude.com
