Shimmy – 5MB privacy-first, local alternative to Ollama (680MB)
⚡ Pure-Rust WebGPU inference engine — OpenAI-API compatible, GGUF native, runs on any GPU. No Python. No llama.cpp. Single binary. - Michael-A-Kuykendall/shimmy
Shimmy – 5MB privacy-first, local alternative to Ollama (680MB) launched on September 4, 2025 with 14 votes, #746 of 8,160 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Shimmy is a lightweight AI tool that runs locally on your computer, using just 5MB compared to Ollama's 680MB. It prioritizes privacy by keeping all data on your device rather than sending it to external servers. The tool is designed for anyone who wants to run AI models locally without significant storage overhead or concerns about data privacy. It's available as open-source software on GitHub.
written from the facts on this page · September 2026
From the sources
Two 5,200-token runs. Same model. SHA-identical byte output. That's a proof, not a benchmark. Shimmy v2.0 ships Airframe: pure-Rust GPU inference with hand-written WGSL compute shaders. No llama.cpp. No C. No Python. No CUDA. First production GGUF engine Rust all the way down — including the GPU shaders. Run TinyLlama, Llama 3.2, Phi, DeepSeek from GGUF. Drop-in for AnythingLLM, Open WebUI, Cursor, Zed via OpenAI or Ollama API. Windows, macOS, Linux. cargo install shimmy
Does a similar job
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We made our own inference engine for Apple Silicon2025 · github.com · ▲186We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.
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I put an AI agent on a $7/month VPS with IRC as its transport layerMar 2026 · georgelarson.me · ▲340The stack: two agents on separate boxes. The public one (nullclaw) is a 678 KB Zig binary using ~1 MB RAM, connected to an Ergo IRC server. Visitors talk to it via a gamja web client embedded in my site. The private one (ironclaw) handles email and scheduling, reachable only over Tailscale via Google's A2A protocol. Tiered inference: Haiku 4.5 for conversation (sub-second, cheap), Sonnet 4.6 for tool use (only when needed). Hard cap at $2/day. A2A passthrough: the private-side agent borrows the gateway's own inference pipeline, so there's one API key and one billing relationship…

Timber – Ollama for classical ML models, 336x faster than PythonMar 2026 · github.com · ▲207Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference. - kossisoroyce/timber
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