What are the hardware requirements for Literature 3B 4096?

Literature 3B 4096 requires approximately 11.7 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Literature 3B 4096 and how large is it?

Literature 3B 4096 is developed by hakurei, a model with 3b 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 Literature 3B 4096?

Literature 3B 4096 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Literature 3B 4096 by hakurei — VRAM 11.7GB, 4K context

Name: Literature 3B 4096
Author: hakurei

Literature 3B 4096 is an open-source language model by hakurei. Features: 3b LLM, VRAM: 11.7GB, Context: 4K, License: mit, LLM Explorer Score: 0.07.

En Endpoints compatible Gpt neox Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/hakurei/Literature-3B-4096

Literature 3B 4096 Parameters and Internals

Model Type

causal-lm

Use Cases

Primary Use Cases:

Entertainment purposes, Creative writing assistant for fiction writers

Training Details

Data Sources:

Gutenberg Project

Data Volume:

2GB

Methodology:

Annotated fiction dataset with prepended tags

Context Length:

4096

LLM Name	Literature 3B 4096
Repository 🤗	https://huggingface.co/hakurei/Literature-3B-4096
Model Size	3b
Required VRAM	11.7 GB
Updated	2026-08-07
Maintainer	hakurei
Model Type	gpt_neox
Model Files	10.4 GB: 1-of-2 1.3 GB: 2-of-2 0.0 GB
Supported Languages	en
Model Architecture	GPTNeoXForCausalLM
License	mit
Context Length	4096
Model Max Length	4096
Transformers Version	4.28.1
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50432
Torch Data Type	float32

Rank the Literature 3B 4096 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

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Note: green Score (e.g. "73.2") means that the model is better than hakurei/Literature-3B-4096.