What are the hardware requirements for Oasst Pythia 12B Reference?

Oasst Pythia 12B Reference requires approximately 23.8 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 Oasst Pythia 12B Reference and how large is it?

Oasst Pythia 12B Reference is developed by dvruette, a model with 12b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Oasst Pythia 12B Reference perform on standard benchmarks?

Oasst Pythia 12B Reference has the following published scores: MMLU 28.33. Compare against reference models on this page or on the LLM Explorer leaderboards.

Oasst Pythia 12B Reference by dvruette — VRAM 23.8GB, 2K context

Name: Oasst Pythia 12B Reference
Author: dvruette

Oasst Pythia 12B Reference is an open-source language model by dvruette. Features: 12b LLM, VRAM: 23.8GB, Context: 2K, LLM Explorer Score: 0.11, Arc: 43, HellaSwag: 67.9, MMLU: 28.3, GSM8K: 1.2.

Endpoints compatible Gpt neox Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/dvruette/oasst-pythia-12b-reference

Oasst Pythia 12B Reference Parameters and Internals

Model Type

text generation

Training Details

Data Sources:

Publicly available datasets

Methodology:

Supervised fine-tuning

Model Architecture:

Transformer-based

Input Output

Input Format:

Text input

Accepted Modalities:

text

Output Format:

Text output

LLM Name	Oasst Pythia 12B Reference
Repository 🤗	https://huggingface.co/dvruette/oasst-pythia-12b-reference
Model Size	12b
Required VRAM	23.8 GB
Updated	2026-05-06
Maintainer	dvruette
Model Type	gpt_neox
Model Files	10.0 GB: 1-of-3 9.9 GB: 2-of-3 3.9 GB: 3-of-3
Model Architecture	GPTNeoXForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.28.0.dev0
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50288
Torch Data Type	float16

Rank the Oasst Pythia 12B Reference 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 Oasst Pythia 12B Reference

Best Alternatives	Context / RAM	Downloads	Likes
Dolly V2 12B	2K / 23.8 GB	3283	1955
...sst Sft 4 Pythia 12B Epoch 3.5	2K / 23.8 GB	818	368
Pythia 12B	2K / 23.8 GB	147000	145
Oasst Rl 1 Pythia 12B	2K / 23.8 GB	10	4
...st Sft 3 Pythia 12B Epoch 2.35	2K / 23.8 GB	10	0
Pythia 12B Deduped	2K / 23.8 GB	4172	53
Oasst Sft 1 Pythia 12B	2K / 23.8 GB	301	277
Pythia 12B Sft V8 7K Steps	2K / 23.8 GB	1106	22
H2ogpt Oasst1 512 12B	2K / 23.9 GB	242	29
Pythia 12B Pre V8.12.5K Steps	2K / 23.8 GB	76	6

Note: green Score (e.g. "73.2") means that the model is better than dvruette/oasst-pythia-12b-reference.