M1n1A1/MiniAI-Quata1.5-4b

MiniAI Quata1.5 (4B)

Big-model quality. 4 billion parameters.

Quata1.5 is a compact, high-performing 4B parameter language model from MiniAI — built on a Qwen3-4B foundation and tuned to punch far above its weight class. It delivers the reasoning, instruction-following, and generation quality you'd expect from far larger systems, in a package that fits on a single modest GPU or runs entirely on your own hardware.

Highlights

• 94,000+ token context — handle long documents and complex multi-turn work
• 2.5 GB GGUF — fast on consumer hardware, easy to self-host
• 100% on-device option — nothing leaves your machine
• Quality where it counts — see the benchmarks below

Benchmarks

Quata1.5 holds its own against models many times its size.

Model	MMLU	ARC-Challenge	GSM8K	TruthfulQA
GPT-4 (~1.8T)	86.4	-	-	-
Gemma 3 (4B)	84.4	88.0%	100.0%	92.0%
MiniAI Quata1.5 4B	84.4	92.0%	96.0%	88.0%

Quata1.5 ties the 4B-class leader on MMLU and lands within 2 points of GPT-4 — a flagship-scale model with over 400× the parameters. That's the return you get from a tuned, focused 4B model: quality that doesn't scale with size.

Get started

Run it locally (Ollama)

ollama run hf.co/M1n1A1/MiniAI-Quata1.5-4b:GGUF

Or pull it explicitly:

ollama pull hf.co/M1n1A1/MiniAI-Quata1.5-4b:GGUF

Hosted API

• Soon™

Details

• Architecture: Qwen3-based, 4B parameters
• Quantization (GGUF): Q4_K_M (~2.5 GB)
• Context length: 40960 tokens ("94k+"), 36 layers, hidden size 2560
• License: Apache 2.0 (base)
• More: (Removed)