---
title: EXEAON AI — Organization Profile Card
colorFrom: indigo
colorTo: blue
sdk: static
pinned: true
---
# EXEAON
### *Frontier models on the hardware you already own.*
[](https://zenuxplimver.tech)
[](https://github.com/ExeaonLM)
[](https://opensource.org/licenses/Apache-2.0)
---
## The problem we work on
At batch one, a language model reads **every weight from memory to produce a
single token**, and uses each weight exactly once. Arithmetic intensity is about
**0.5 FLOP per byte**, so generation speed is:
> **tokens/second ≤ memory bandwidth ÷ model bytes**
The accelerator's FLOP rating never enters that equation. A 7B model in bf16 is
14 GB — on 1 TB/s that is a hard ceiling near 71 tokens per second, whatever the
spec sheet claims. The only lever on single-stream speed is how many bytes the
model is.
**So we move fewer bytes.** ℰ-PURE compresses the weights, and they stay
compressed in memory — packed indices go straight into the matmul, where the
kernel decodes them in the operand path. The dense weight is never assembled.
That is the difference between a smaller download and a smaller *process*.
See it for yourself: **[The Memory Wall](https://huggingface.co/spaces/Exeaon/memory-wall)** —
pick your hardware, pick a model size, watch the ceiling move.
---
## The families
| class | say it | meaning | runs on | sizes |
|---|---|---|---|---|
| **Dzo** | *jo* | fire (Ewe) | laptop, CPU, edge | ≤ 4B |
| **Nunya** | *NOO-nya* | knowledge (Ewe) | a single GPU | 7B – 32B |
| **Kese** | *KEH-seh* | great (Twi) | server, multi-GPU, MoE | 70B+ |
Fire, knowledge, greatness — named in Ewe and Twi, from Ghana, where we build.
Every model is published **compressed by default**. The uncompressed reference
carries the `-BF16` suffix, not the other way round: running on less hardware is
the product, not a variant of it.
---
## What is free, and what is not
| | |
|---|---|
| **Free and open (Apache-2.0)** | the `epure-runtime` library, CLI and SDK · the `.ebin` format specification · every published model weight |
| **Ours** | the ℰ-PURE encoder — the compressor that produces them |
You can run, fine-tune, serve, benchmark and deploy anything we publish without
asking us and without paying us. What we keep is the compressor itself.
```bash
pip install epure-runtime
epure run Exeaon/Exeaon-Dzo-1.7B --prompt "Explain the memory wall."
```
---
## Fine-tuning without decompressing
Compressed models here are not frozen artifacts. The quantization indices stay
fixed while the codebook and per-group scales train — roughly 1% of the weight
values — so adaptation happens **in the compressed state**, never by rebuilding
the dense weight in memory.
Gradients through the packed representation are exact, verified against a dense
reference to within 2×10⁻⁶.
---
## Attribution
Several Exeaon models are derived from openly licensed base models (Apache-2.0
or MIT). Each model card names its base model, links the original, and ships the
upstream `LICENSE` and `NOTICE` files unmodified, as those licences require.
Compression, calibration, packaging and the runtime are ours. The pretrained
knowledge is not, and we say so on every card.
---
## Connect
- **Runtime and SDK** — [github.com/ExeaonLM](https://github.com/ExeaonLM)
- **Website** — [zenuxplimver.tech](https://zenuxplimver.tech)
- **Contact** — contact@zenuxplimver.tech
EXEAON is a product of Zenux Plimver Technologies LTD, Ghana.