What are the hardware requirements for Cowboy?

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

Who developed Cowboy and how large is it?

Cowboy is developed by QuillBytes, 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 Cowboy?

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

Cowboy by QuillBytes — VRAM 0.7GB

Name: Cowboy
Author: QuillBytes

Cowboy is an open-source language model by QuillBytes. Features: 4b LLM, VRAM: 0.7GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.32.

Base model:adapter:qwen/qwen3.... Base model:qwen/qwen3.5-4b Cowboy En Endpoints compatible Finetuned Fun Gguf Image-text-to-text Lora Quantized Qwen3.5 Qwen3 5 Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/QuillBytes/cowboy

Cowboy Parameters and Internals

LLM Name	Cowboy
Repository 🤗	https://huggingface.co/QuillBytes/cowboy
Base Model(s)	Qwen/Qwen3.5-4B Qwen/Qwen3.5-4B
Model Size	4b
Required VRAM	0.7 GB
Updated	2026-09-17
Maintainer	QuillBytes
Model Type	qwen3_5
Model Files	0.7 GB 2.8 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0

Rank the Cowboy 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 Cowboy

Best Alternatives	Context / RAM	Downloads	Likes
... Opus Reasoning Distilled GGUF	0K / 0.7 GB	338962	154
Dahono 4B	0K / 9.3 GB	2042	2
IDK V1	0K / 2.7 GB	764	5
Qwen3.5 4B Cybertune	0K / 9.3 GB	476	1
Nomi 2 GGUF	0K / 0.7 GB	755	1
Peacock Tiny 4B Gguf	0K / 0.7 GB	49	1
Underdog Woof 4B 1.1	0K / 2.4 GB	418	13
Qwen3.5 4B MLX 4bit	0K / 3 GB	28023	32
Qwen3.5 4B 4bit Abliterated	0K / 3 GB	85	1
Huihui Qwen3.5 4B Abliterated	0K / 9.1 GB	10166	35

Note: green Score (e.g. "73.2") means that the model is better than QuillBytes/cowboy.