Reame – a CPU inference server that gets faster as it runs
CPU-first LLM inference server on llama.cpp. Runs useful models on free-tier ARM boxes; rewriting the input made it ~6x faster and more accurate than tuning the engine. MIT, benchmarks and failures included. - swellweb/reame
Reame – a CPU inference server that gets faster as it runs launched on July 11, 2026 with 59 votes, #592 of 24,623 launches that month and more than 95% of that year's launches.
In plain words
Reame is a CPU inference server designed for developers and teams who need to run machine learning models on standard processors. It's built to improve performance over time as it executes, optimizing how it handles repeated inference tasks. The server runs entirely on CPU rather than requiring specialized hardware, making it accessible for various deployment scenarios. It's available as open-source software on GitHub.
written from the facts on this page · September 2026
From the sources
Reame is a CPU-first LLM inference server on llama.cpp with an OpenAI-compatible API. Built for narrow, repetitive workloads on cheap hardware — a €5 VPS, a free tier, a 2-core ARM box. Its memory layer caches prompts, prefixes and past generations to disk, so request #100 costs a fraction of request #1. MIT.
▶ Try the live demo — a real Reame instance serving an LLM from a free Oracle ARM box, directly in your browser. Reame is an LLM server designed for ordinary CPUs, specifically built around ternary models — where weights are strictly −1, 0, or +1. You can run an 8-billion-parameter model in just 2.2 GB on a free-tier cloud instance, using a custom engine that actually outperforms the model vendor's own runtime. These aren't just marketing claims; they are measured. Running Bonsai-8B (PrismML's ternary flagship) against PrismML's own llama.cpp fork on the same hardware, using identical prompts and clean environments: The bold figures are medians of three back-to-back runs; the full protocol…from github.com
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