What are the hardware requirements for Gpt2 Xl?

Gpt2 Xl requires approximately 6.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gpt2 Xl and how large is it?

Gpt2 Xl is developed by huggingface.co, a model with 1.6b 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 Gpt2 Xl?

Gpt2 Xl is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gpt2 Xl by huggingface.co — VRAM 6.4GB

Name: Gpt2 Xl
Author: huggingface.co

Gpt2 Xl is an open-source language model by huggingface.co. Features: 1.6b LLM, VRAM: 6.4GB, License: mit, LLM Explorer Score: 0.09.

Arxiv:1910.09700 Deploy:azure En Endpoints compatible Gpt2 Jax Pytorch Region:us Rust Safetensors Tf

Model Card on HF 🤗: https://huggingface.co/openai-community/gpt2-xl

Gpt2 Xl Parameters and Internals

Model Type

Transformer-based language model, Pre-trained, text generation

Use Cases

Areas:

Research, AI, Commercial applications

Applications:

Writing assistance, Grammar assistance, Autocompletion, Creative writing and art, Entertainment, Chat bots, Games

Primary Use Cases:

Language understanding and generation

Limitations:

Unsuitable for factually accurate text generation, Known biases

Considerations:

Awareness of biases and limitations is required for intended usages

Additional Notes

Environmental impact details highlighted with carbon emissions calculator insights available.

Supported Languages

English (fluent)

Training Details

Data Sources:

WebText, a dataset scraped from outbound links on Reddit with at least 3 karma

Data Volume:

40GB of text

Methodology:

Pretraining with causal language modeling objective

Context Length:

1024

Training Time:

168 hours

Hardware Used:

32 TPUv3 chips

Model Architecture:

Transformer-based, pretrained

Responsible Ai Considerations

Fairness:

Known biases in training data, significant research into bias and fairness

Transparency:

Green AI considerations discussed

Mitigation Strategies:

Users should carry out a study of biases relevant to their intended use-case

Input Output

Input Format:

Tokenized using a byte-level version of Byte Pair Encoding with a vocabulary size of 50,257

Accepted Modalities:

text

Output Format:

Text generation

Performance Tips:

Setting a random seed improves reproducibility of text generation

LLM Name	Gpt2 Xl
Repository 🤗	https://huggingface.co/openai-community/gpt2-xl
Model Size	1.6b
Required VRAM	6.4 GB
Updated	2026-05-19
Maintainer	huggingface.co
Model Type	gpt2
Model Files	6.4 GB 6.4 GB
Supported Languages	en
Model Architecture	GPT2LMHeadModel
License	mit
Model Max Length	1024
Vocabulary Size	50257
Activation Function	gelu_new

Rank the Gpt2 Xl 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

Quantized Models of the Gpt2 Xl

Model	Likes	Downloads	VRAM
MicroLLM2	1	244	1 GB

Best Alternatives to Gpt2 Xl

Best Alternatives	Context / RAM	Downloads	Likes
BananaMind 1.0 Instruct	0K / 6.2 GB	24	0
Gpt2 Chatbot	0K / 6.3 GB	19	14
Intellect V0.2 1.6B	0K / 6.3 GB	44	1
Intellect V0.3 1.6B	0K / 6.3 GB	23	1
BetterGPT2	0K / 3.1 GB	5	0
Gpt2 Xl Lima	0K / 3.1 GB	232	0
Gpt2o Chatbot 03	0K / 3.1 GB	16	0
Gpt2o Chatbot 09	0K / 3.1 GB	7	0
Gpt2o Chatbot 11	0K / 3.1 GB	6	0
Gpt2o Chatbot 02	0K / 3.1 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than openai-community/gpt2-xl.