What are the hardware requirements for Nomi 2 GGUF?

Nomi 2 GGUF requires approximately 0.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nomi 2 GGUF and how large is it?

Nomi 2 GGUF is developed by JallyAI, a model with 4b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Nomi 2 GGUF?

Nomi 2 GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nomi 2 GGUF by JallyAI — VRAM 0.7GB

Name: Nomi 2 GGUF
Author: JallyAI

Nomi 2 GGUF is an open-source language model by JallyAI. Features: 4b LLM, VRAM: 0.7GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.28.

Base model:jallyai/nomi-2 Base model:quantized:jallyai/n... Conversational Efficient Endpoints compatible Gguf Image-text-to-text Lazyloopstudio Nomi Nomi2 Quantized Qwen Qwen3.5 Qwen3 5 Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/JallyAI/Nomi-2-GGUF

Nomi 2 GGUF Parameters and Internals

LLM Name	Nomi 2 GGUF
Repository 🤗	https://huggingface.co/JallyAI/Nomi-2-GGUF
Model Name	unsloth/Qwen3.5-4B
Base Model(s)	Nomi 2 JallyAI/Nomi-2
Model Size	4b
Required VRAM	0.7 GB
Updated	2026-08-09
Maintainer	JallyAI
Model Type	qwen3_5
Model Files	0.7 GB 2.0 GB 2.3 GB 2.8 GB 3.6 GB 4.6 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Torch Data Type	float16

Rank the Nomi 2 GGUF capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Nomi 2 GGUF

Best Alternatives	Context / RAM	Downloads	Likes
... Opus Reasoning Distilled GGUF	0K / 0.7 GB	338962	154
Dahono 4B	0K / 9.3 GB	2300	3
Cowboy	0K / 0.7 GB	529	1
Shakespeare	0K / 0.7 GB	481	1
Cowboy	0K / 0.7 GB	646	1
IDK V1	0K / 2.7 GB	333	5
Qwen3.5 4B Cybertune	0K / 9.3 GB	476	1
Peacock Tiny 4B Gguf	0K / 0.7 GB	52	1
Underdog Woof 4B 1.1	0K / 2.4 GB	1141	18
Qwen3.5 4B MLX 4bit	0K / 3 GB	28023	32

Note: green Score (e.g. "73.2") means that the model is better than JallyAI/Nomi-2-GGUF.