TokenAI aims to deliver the strongest language models in the world and in the Arab world through the Horus family of models. The startup bridges the gap between cutting-edge AI capabilities and regional cultural contexts, starting with the Arab world.

The Horus Family

Horus-1.0-4B marks the first model in the Horus family line. This is just the beginning of TokenAI's journey to create a comprehensive suite of AI models serving the Arab region.

Horus-1.0-4B-GGUF

GGUF quantized versions of Horus-1.0-4B - A 4B parameter multilingual language model optimized for Arabic and English.

Model Variants & Hardware Requirements

Format	File Size	Min RAM (CPU)	Min VRAM (GPU)	Quality	Best For
F16	9.03 GB	12 GB	10 GB	Maximum quality	High-end GPUs (RTX 3090, A100)
Q8_0	4.8 GB	6 GB	5 GB	Near-lossless	RTX 3060 12GB, RTX 4060
Q6_K	3.71 GB	5 GB	4 GB	Excellent	RTX 3060, RTX 4060 Laptop
Q5_K_M	3.23 GB	4 GB	3.5 GB	Very Good	GTX 1650, RTX 3050
Q4_K_M	2.78 GB	3.5 GB	3 GB	Good	Entry-level GPUs, CPU-only

Detailed Hardware Requirements

F16 (FP16 - Full Precision)

File: Horus-1.0-4B-F16.gguf (9.03 GB)
Min System RAM: 12 GB
Min VRAM: 10 GB
Recommended: RTX 3090, RTX 4090, A100, A6000
Use Case: Maximum quality, research, fine-tuning reference

Q8_0 (8-bit Quantization)

File: Horus-1.0-4B-Q8_0.gguf (4.8 GB)
Min System RAM: 6 GB
Min VRAM: 5 GB
Recommended: RTX 3060 12GB, RTX 4060, RTX 4070
Use Case: Near-lossless quality with half the memory

Q6_K (6-bit K-Quant)

File: Horus-1.0-4B-Q6_K.gguf (3.71 GB)
Min System RAM: 5 GB
Min VRAM: 4 GB
Recommended: RTX 3060, RTX 4060 Laptop, GTX 1080 Ti
Use Case: Excellent quality for most applications

Q5_K_M (5-bit K-Quant Medium)

File: Horus-1.0-4B-Q5_K_M.gguf (3.23 GB)
Min System RAM: 4 GB
Min VRAM: 3.5 GB
Recommended: GTX 1650 Super, RTX 3050, RTX 3050 Ti
Use Case: Balanced quality and performance

Q4_K_M (4-bit K-Quant Medium)

File: Horus-1.0-4B-Q4_K_M.gguf (2.78 GB)
Min System RAM: 3.5 GB
Min VRAM: 3 GB
Recommended: GTX 1060 6GB, GTX 1650, Intel Arc A380
Use Case: Maximum compression, edge devices, CPU inference

Quick Start

Using NeuralNode (Recommended)

The easiest way to use Horus GGUF models is with the NeuralNode framework:

python

import neuralnode as nn

MODEL_ID = "tokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-Q6_K.gguf"
DEVICE = "cpu"  # Change to "cuda" for GPU acceleration

# Download and load
model = nn.HorusModel(MODEL_ID, device=DEVICE).load()

# Use immediately
response = model.chat([{"role": "user", "content": "hi horus im emy"}])
print(response.content)

Using llama-cpp-python

For direct llama.cpp integration:

python

from llama_cpp import Llama

llm = Llama(
    model_path="Horus-1.0-4B-Q4_K_M.gguf",
    n_ctx=4096
)

output = llm("Hello, how are you?", max_tokens=256)
print(output['choices'][0]['text'])

Voice Interface with Replica TTS

Add natural voice output to your Horus GGUF model with Replica TTS:

python

import neuralnode as nn

voice_id = "replica-aria-language{en-us}"

MODEL_ID = "tokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-F16.gguf"
DEVICE = "cuda"

# Load model with Replica TTS
model = nn.HorusModel(
    MODEL_ID,
    tts_engine="replica_tts",
    voice=voice_id,
    device=DEVICE
).load()

# Chat and get spoken response
response = model.chat([{"role": "user", "content": "Hello!"}])
print(response.content)
response.play_audio()  # Plays the TTS audio

Browse All Voices

python

import neuralnode as nn

voices = nn.replica_voice_list()
for voice in voices:
    print(voice)

Benchmark Results

Below are visual comparisons of Horus-1.0-4B against leading models.

General Knowledge & Reasoning

Arabic Language & Cultural Benchmarks

Coding & Tool Use Benchmarks

Model Capabilities

Multilingual: Supports 10+ languages including Arabic, English, French, Spanish, German, Italian, Portuguese, Turkish, Urdu, Hindi
Identity Recognition: Knows itself as Horus from TokenAI
Reasoning: Chain-of-thought capabilities
Context Length: Up to 4096 tokens
Voice Output: Replica TTS integration for natural speech

tokenaii/Horus-1.0-4B-GGUF

Hours-1.0-4B-GGUF

Base Model

About TokenAI

Mission

The Horus Family

Horus-1.0-4B-GGUF

Model Variants & Hardware Requirements

Detailed Hardware Requirements

F16 (FP16 - Full Precision)

Q8_0 (8-bit Quantization)

Q6_K (6-bit K-Quant)

Q5_K_M (5-bit K-Quant Medium)

Q4_K_M (4-bit K-Quant Medium)

Quick Start

Using NeuralNode (Recommended)

Using llama-cpp-python

Voice Interface with Replica TTS

Browse All Voices

Benchmark Results

General Knowledge & Reasoning

Arabic Language & Cultural Benchmarks

Coding & Tool Use Benchmarks

Model Capabilities

Links

tokenaii/
Horus-1.0-4B-GGUF