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license: apache-2.0
tags:
- llama.cpp
- gguf
- local-ai
- inference
- mixture-of-experts
- vulkan
- rocm
- metal
- text-to-image
- text-to-speech
- text-to-audio
- text-to-video
Kera
A local AI engine and app, built on llama.cpp, that runs big models fast on your own computer.
By Kera Labs. Version v0.1.1: 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 automeasures 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-userreads 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. - Pictures, music, speech and video, on your computer too (0.1.1). Vision models get their image reader by
themselves;
kera imageandkera serverun image models (SD, SDXL, SD3.5, FLUX, Qwen-Image, Z-Image) through stable-diffusion.cpp, andkera videovideo models (Wan, LTX-Video);kera musicmakes songs with ACE-Step 1.5 through acestep.cpp, lyrics included;kera speakturns text into speech with Qwen3-TTS. Each engine comes in the download, and the models are yours to download.
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.
As accurate as the usual way
Speed doesn't cost accuracy. One model file (Qwen2.5-1.5B-Instruct) through Kera and through Ollama 0.40.15,
200 questions with known answers (100 school maths problems from GSM8K, 100 science questions from
ARC-Challenge), greedy: Kera 149 right, Ollama 147; both give the model the same prompt, token for token.
Pictures made with SD-Turbo through Kera and through the model's own reference code (Hugging Face diffusers),
with the same seed and weights, look identical (46.7 dB alike). Details: docs/QUALITY.md in the source.
Downloads
| File | For |
|---|---|
downloads/kera-v0.1.1-windows-x64.zip |
Windows 10 and 11 (Vulkan: AMD, NVIDIA and Intel graphics, or the CPU) |
downloads/kera-v0.1.1-windows-x64-hip-addon.zip |
Optional: AMD's ROCm for Radeon 8060S (gfx1151), unzipped into the same folder |
downloads/kera-v0.1.1-linux-x64.tar.gz |
Linux (Vulkan or the CPU) |
downloads/kera-v0.1.1-macos-arm64.zip |
Mac with Apple silicon (Metal), macOS 13.3 or later |
downloads/Kera-vs-Ollama.dmg |
A Mac app that races Kera against Ollama on your Mac, live, with one button |
source/kera-v0.1.1-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).

