What are the hardware requirements for Opt 2.7B?

Opt 2.7B requires approximately 5.3 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 Opt 2.7B and how large is it?

Opt 2.7B is developed by facebook, a model with 2.7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Opt 2.7B perform on standard benchmarks?

Opt 2.7B has the following published scores: MMLU 25.43. Compare against reference models on this page or on the LLM Explorer leaderboards.

Opt 2.7B by facebook — VRAM 5.3GB, 2K context

Name: Opt 2.7B
Author: facebook

Opt 2.7B is an open-source language model by facebook. Features: 2.7b LLM, VRAM: 5.3GB, Context: 2K, License: other, LLM Explorer Score: 0.1, Arc: 34, HellaSwag: 61.4, MMLU: 25.4, GSM8K: 0.2.

Arxiv:2005.14165 Arxiv:2205.01068 En Jax Opt Pytorch Region:us Tf

Model Card on HF 🤗: https://huggingface.co/facebook/opt-2.7b

Opt 2.7B Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

research, downstream tasks evaluation, text generation

Primary Use Cases:

prompting for evaluation, fine-tuning on a downstream task

Limitations:

bias and safety issues, generation diversity and hallucination issues

Supported Languages

English (predominantly supported)

Training Details

Data Sources:

CommonCrawl, BookCorpus, CC-Stories, The Pile, Pushshift.io Reddit, CCNewsV2

Data Volume:

180B tokens

Methodology:

causal language modeling objective

Context Length:

2048

Training Time:

~33 days on 992 *80GB A100 GPUs

Hardware Used:

992 *80GB A100 GPUs

Model Architecture:

decoder-only

LLM Name	Opt 2.7B
Repository 🤗	https://huggingface.co/facebook/opt-2.7b
Model Size	2.7b
Required VRAM	5.3 GB
Updated	2026-07-26
Maintainer	facebook
Model Type	opt
Model Files	5.3 GB
Supported Languages	en
Model Architecture	OPTForCausalLM
License	other
Context Length	2048
Model Max Length	2048
Transformers Version	4.21.0.dev0
Beginning of Sentence Token	</s>
End of Sentence Token	</s>
Unk Token	</s>
Vocabulary Size	50272
Torch Data Type	float16
Activation Function	relu
Errors	replace

Rank the Opt 2.7B 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 Opt 2.7B

Best Alternatives	Context / RAM	Downloads	Likes
LLmRa 2.7B	2K / 10.6 GB	642	1
OPT 2.7B Nerybus Mix	2K / 5.5 GB	194	10
OPT 2.7B Erebus	2K / 5.3 GB	380	42
OPT 2.7B Nerys V2	2K / 5.3 GB	124	6
Opt 2.7B Realtime Chat V2	2K / 11.1 GB	9	0
LongForm OPT 2.7B	2K / 5.3 GB	5	3
Opt 2.7B Wikitext2	2K / 11.1 GB	6	0
Opt 2.7B Realtime Chat	2K / 11.1 GB	7	2
Opt Peter 2.7B	2K / 10.6 GB	2	2
Opt 2.7B AWQ	2K / 1.6 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than facebook/opt-2.7b.