Horus Hiero 4B Mini is an advanced language model developed by TokenAI, an Egyptian AI startup founded by Assem Sabry. The model specializes in understanding and translating ancient Egyptian Hieroglyphs into various modern human languages. In addition, it is highly multilingual and masters 150 Languages + Hieroglyphic. To ensure accessibility and efficient deployment across different hardware setups, the model is also available in multiple GGUF variants.
Model Overview
Horus Hiero 4B Mini is a 4-billion parameter language model built on top of the robust Qwen/Qwen3.5-4B architecture (or its GGUF equivalent). It is designed to handle extremely long contexts and leverages a sophisticated hybrid attention mechanism to deliver high performance and efficiency.
Leading Model in the Middle East
Middle East Top Models
150 Languages + Hieroglyphic
Languages
Example: Hieroglyph Translation
Translation Example
Model Variants
The following quantized versions are available for different deployment scenarios:
Enabled (toggleable via enable_thinking parameter)
Benchmark Results
Benchmark
Score
MMLU-Pro
74.2%
GPQA Diamond
72.3%
HumanEval
68.2%
LiveCodeBench
51.4%
MATH
45.8%
Quick Start
Using NeuralNode (Recommended)
The easiest way to use Horus models is with the NeuralNode framework:
python
1import neuralnode as nn
23# For GGUF models (recommended):4MODEL_ID ="tokenaii/Horus-Hiero-Mini-4B-GGUF/Horus-Hiero-Mini-4B-Q6_K.gguf"5DEVICE ="cpu"# Change to "cuda" for GPU acceleration67# Download and load8model = nn.HorusModel(MODEL_ID, device=DEVICE).load()910# Use immediately11response = model.chat([12{"role":"user","content":"Translate this hieroglyph: 𓂋𓏏𓈖𓀀"}13])14print(response.content)
TokenAI is a non-profit AI startup founded in 2025 by Assem Sabry, located in Alexandria, Egypt.
The Horus family is our line of advanced language models. The series began with Horus 1.0 4B, which achieved remarkable success as the very first language model to be fully trained from scratch in Egypt. Building on that foundation, Horus Hiero brings specialized capabilities in ancient languages while retaining powerful modern multilingual performance.