🌌 Noir-Ultra (7B)

Name: Noir-Ultra
Availability: InStock

Noir Family | GGUF Versions | Technical Report

Noir-Ultra is the elite 7-billion parameter model of the Noir series. It represents a breakthrough in training efficiency: where previous 7B iterations required 6 epochs to reach stability, Noir-Ultra achieved superior results in just a single epoch.

This model is a "compact titan," delivering scientific reasoning and mathematical accuracy that rival much larger architectures.

🚀 The Ultra Advantage

🧬 Unrivaled STEM: With a 91.0% score on SciQ, it is a specialized tool for scientific inquiry.
📐 Mathematical Precision: Scoring 84.0% on GSM8K, it handles complex chains of thought with ease.
🧠 Logical Depth: An ARC-Challenge score of 86.0% places it at the top of its weight class for reasoning tasks.

📊 Evaluation Dashboard (Noir Ultra Report)

Based on the latest evaluation, Noir-Ultra shows an exceptionally strong profile in technical domains:

Domain	Benchmark	Result (%)	Status
STEM	SciQ	91.0%	🏆 Master
Logic	ARC-C	86.0%	🔥 Elite
Math	GSM8K	84.0%	✅ Advanced
Medicine	MedQA	65.0%	🩺 Competent
Physics	MMLU-Physics	70.0%	🧪 Specialist

📦 Noir Model Family Matrix

Model	Parameters	Role	Key Strength
Noir-Lightning	0.5B	The Pocket Assistant	Ultra-fast, runs on anything
Noir-Mini	1.5B	The Balanced Thinker	High speed with solid grammar
Noir-Standard	3B	The Versatile Workhorse	65% GSM8K, perfect for 8GB VRAM
Noir-Ultra	7B	The Reasoning Master	91% SciQ & 84% Math
Noir-Starlight	14B	The Galactic Intelligence	Deep logic & Expert-level STEM

🛠 Quick Start (Transformers)

python

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "muverqqw/Noir-Ultra" 
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name, 
    load_in_4bit=True, # Recommended for 8GB VRAM
    device_map="auto"
)

👤 Credits

Developer: IceL1ghtning
Architecture: Qwen 2.5 (7B)
Release: 2026
License: Apache 2.0

_{Efficiency meets intelligence. Built with passion for the open-source community.}