What are the hardware requirements for Bilingual GPT Neox 4B?

Bilingual GPT Neox 4B requires approximately 7.7 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Bilingual GPT Neox 4B and how large is it?

Bilingual GPT Neox 4B is developed by rinna, a model with 4b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Bilingual GPT Neox 4B perform on standard benchmarks?

Bilingual GPT Neox 4B has the following published scores: MMLU 23.1. Compare against reference models on this page or on the LLM Explorer leaderboards.

Bilingual GPT Neox 4B by rinna — VRAM 7.7GB, 2K context

Name: Bilingual GPT Neox 4B
Author: rinna

Bilingual GPT Neox 4B is an open-source language model by rinna. Features: 4b LLM, VRAM: 7.7GB, Context: 2K, License: mit, LLM Explorer Score: 0.14, Arc: 29.2, HellaSwag: 43.7, MMLU: 23.1.

Arxiv:2404.01657 Dataset:cc100 Dataset:eleutherai/pile Dataset:mc4 Dataset:togethercomputer/redpa... Dataset:wikipedia En Gpt neox Ja Pytorch Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/rinna/bilingual-gpt-neox-4b

Bilingual GPT Neox 4B Parameters and Internals

Model Type

bilingual, text generation

Supported Languages

ja (native), en (proficient)

Training Details

Data Sources:

Japanese CC-100, mc4, EleutherAI/pile, togethercomputer/RedPajama-Data-1T, Wikipedia

Data Volume:

524B tokens

Methodology:

36-layer, 2816-hidden-size transformer

Model Architecture:

transformer-based language model

Input Output

Accepted Modalities:

text

Performance Tips:

Since the model is sensitive to decoding hyper-parameters, it is suggested to explore the best setting for your task.

LLM Name	Bilingual GPT Neox 4B
Repository 🤗	https://huggingface.co/rinna/bilingual-gpt-neox-4b
Model Size	4b
Required VRAM	7.7 GB
Updated	2026-07-03
Maintainer	rinna
Model Type	gpt_neox
Model Files	7.7 GB 7.7 GB
Supported Languages	ja en
Model Architecture	GPTNeoXForCausalLM
License	mit
Context Length	2048
Model Max Length	2048
Tokenizer Class	T5Tokenizer
Padding Token	[PAD]
Vocabulary Size	65536
Torch Data Type	float16

Rank the Bilingual GPT Neox 4B capabilities

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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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