What are the hardware requirements for Pythia 6.9B?

Pythia 6.9B requires approximately 13.8 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 Pythia 6.9B and how large is it?

Pythia 6.9B is developed by EleutherAI, a model with 6.9b 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 Pythia 6.9B?

Pythia 6.9B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Pythia 6.9B by EleutherAI — VRAM 13.8GB, 2K context

Name: Pythia 6.9B
Author: EleutherAI

Pythia 6.9B is an open-source language model by EleutherAI. Features: 6.9b LLM, VRAM: 13.8GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.12.

Arxiv:2101.00027 Arxiv:2201.07311 Arxiv:2304.01373 Dataset:eleutherai/pile Deploy:azure En Endpoints compatible Gpt neox Pythia Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/EleutherAI/pythia-6.9b

Pythia 6.9B Parameters and Internals

Model Type

transformer-based, language model

Use Cases

Areas:

Research, Scientific Experiments

Primary Use Cases:

Behavior and functionality study of large language models

Limitations:

Not intended for deployment, May produce harmful or offensive text, English-language only

Considerations:

Conduct risk and bias assessment before use.

Additional Notes

Non-embedding parameters: 6,444,163,072.

Supported Languages

English (Fluent)

Training Details

Data Sources:

the Pile

Data Volume:

299,892,736,000 tokens

Methodology:

Trained on deduplicated and non-deduplicated data, with checkpoints. Same hyperparameters for deduped and non-deduped models.

Model Architecture:

Transformer-based

Release Notes

Version:

Current Release

Date:

January 2023

Notes:

Rename of models. Uniform batch size training. Added early checkpoints. Used Flash Attention.

LLM Name	Pythia 6.9B
Repository 🤗	https://huggingface.co/EleutherAI/pythia-6.9b
Model Size	6.9b
Required VRAM	13.8 GB
Updated	2026-08-08
Maintainer	EleutherAI
Model Type	gpt_neox
Model Files	9.9 GB: 1-of-2 3.9 GB: 2-of-2 9.9 GB: 1-of-2 3.9 GB: 2-of-2
Supported Languages	en
Model Architecture	GPTNeoXForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.24.0
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50432
Torch Data Type	float16

Rank the Pythia 6.9B 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 Pythia 6.9B

Best Alternatives	Context / RAM	Downloads	Likes
...d E2e Alignment Upsampled Base	16K / 13.8 GB	15	0
...2e Misalignment Upsampled Base	16K / 13.8 GB	15	0
...train Alignment Upsampled Base	16K / 13.8 GB	13	1
...d E2e Alignment Upsampled Base	16K / 13.8 GB	14	0
...train Alignment Upsampled Base	16K / 13.8 GB	11	0
Sfm Baseline Unfiltered Base	16K / 13.8 GB	68	0
...in Misalignment Upsampled Base	16K / 13.8 GB	14	0
...raining Mix Blocklist Filtered	16K / 13.8 GB	21	0
Pythia 6.9B Deduped 8K	8K / 13.8 GB	11	1
Pythia 6.9B Deduped	2K / 13.8 GB	15102	7

Note: green Score (e.g. "73.2") means that the model is better than EleutherAI/pythia-6.9b.