What are the hardware requirements for Shakespeare?

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

Who developed Shakespeare and how large is it?

Shakespeare is developed by quill-voice, 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 Shakespeare?

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

Shakespeare by quill-voice — VRAM 0.7GB

Name: Shakespeare
Author: quill-voice

Shakespeare is an open-source language model by quill-voice. Features: 4b LLM, VRAM: 0.7GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.33.

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

Model Card on HF 🤗: https://huggingface.co/quill-voice/shakespeare

Shakespeare Parameters and Internals

LLM Name	Shakespeare
Repository 🤗	https://huggingface.co/quill-voice/shakespeare
Base Model(s)	Qwen/Qwen3-4B Qwen/Qwen3-4B
Model Size	4b
Required VRAM	0.7 GB
Updated	2026-09-22
Maintainer	quill-voice
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 Shakespeare 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 Shakespeare

Best Alternatives	Context / RAM	Downloads	Likes
... Opus Reasoning Distilled GGUF	0K / 0.7 GB	338962	154
Dahono 4B	0K / 9.3 GB	2110	2
Cowboy	0K / 0.7 GB	529	1
Cowboy	0K / 0.7 GB	646	1
IDK V1	0K / 2.7 GB	775	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	39	1
Underdog Woof 4B 1.1	0K / 2.4 GB	675	14
Qwen3.5 4B MLX 4bit	0K / 3 GB	28023	32

Note: green Score (e.g. "73.2") means that the model is better than quill-voice/shakespeare.