Kera

A local AI engine and app, built on llama.cpp, that runs big models fast on your own computer.

By Kera Labs. Version v0.1.0-preview.4, a preview: it works and is measured on real hardware, but not every goal is reached yet (below).

Kera runs the same GGUF model files as llama.cpp and Ollama, and gives exactly the model's own answers unless you turn on a mode that trades a little quality for speed (each one's measured cost is published). What it adds:

• It writes faster. It guesses the next few words ahead by itself where that pays (copying from the chat, the model's own MTP head), measures whether each guesser pays, and drops the ones that don't.
• It picks the fastest back-end for each message. On an AMD machine with the optional ROCm add-on, kera serve --backend auto measures Vulkan and ROCm on each model and sends every message to the one that finishes it sooner: chats to Vulkan, long documents (and their follow-ups) to ROCm.
• Chats survive restarts. Each chat's state is kept on the SSD, so a follow-up or a restart doesn't read the whole conversation again.
• Models bigger than memory. A mixture-of-experts model that doesn't fit is streamed from the SSD, expert by expert, with the experts it uses most kept in memory.
• Several people at once. kera serve --multi-user reads a new message before the rest of someone's long document, keeps everyone writing while a long prompt is read, and reads a start several chats share only once.
• It explains your computer. The first time it starts, it measures your drive, memory and graphics chip in about 30 seconds and says in plain words what you can run.
• OpenAI- and Anthropic-compatible server (kera serve), so existing chat apps and agents work with it.

Measured

On a Minisforum mini PC (AMD Ryzen AI Max, Radeon 8060S graphics, Windows), with Nemotron 3 Nano 30B-A3B (Ollama's own 22.8 GB file, so every engine ran the same weights), October 2026:

	Kera, Vulkan	Kera, ROCm add-on	llama.cpp	Ollama
Writing speed, everyday prompts (tokens a second)	66	54	56	41
First word in a chat	0.36 s	0.32 s	0.38 s	1.1 s
First word after a restart	0.79 s	0.87 s	3.0 s	3.2 s
A 95,000-word document: first word	296 s	138 s	303 s	144 s
Follow-up question on it	0.43 s	0.33 s	0.41 s	2.2 s

Every number has its source, settings and date in docs/BENCHMARKS.md in the source.

Downloads

File	For
downloads/kera-v0.1.0-preview.4-windows-x64.zip	Windows 10 and 11 (Vulkan: AMD, NVIDIA and Intel graphics, or the CPU)
downloads/kera-v0.1.0-preview.4-windows-x64-hip-addon.zip	Optional: AMD's ROCm for Radeon 8060S (gfx1151), unzipped into the same folder
downloads/kera-v0.1.0-preview.4-linux-x64.tar.gz	Linux (Vulkan or the CPU)
downloads/Kera-vs-Ollama.dmg	A Mac app that races Kera against Ollama on your Mac, live, with one button
source/kera-v0.1.0-preview.4-source.tar.gz	The source code

Try it: unzip, run kera (a page opens in your browser and explains your computer), then kera serve -m model.gguf for chat apps (http://127.0.0.1:8080). kera serve --help lists Kera's options.

No model weights are included: Kera runs GGUF files you download (from Hugging Face, or the ones Ollama already has), each under its own licence.

Status

This is a preview. Kera's goals each have a gate measured on real hardware; the Windows machine above has passed some of its measurements, and the rest (the Mac, NVIDIA machines and the bigger models) are still to be measured. The Mac version builds and passes its tests, but hasn't been measured on a Mac yet.

Licence

Kera's own code: Apache License 2.0, copyright Kera Labs (LICENSE). It is built on llama.cpp and ggml (MIT) and bundles other open-source code under its own licences (NOTICE, and THIRD_PARTY_LICENSES.txt in each download).