What are the hardware requirements for Llama 2 7B Chat Hf?

Llama 2 7B Chat Hf requires approximately 13.5 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 2 7B Chat Hf and how large is it?

Llama 2 7B Chat Hf is developed by NousResearch, a model with 7b 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 Llama 2 7B Chat Hf?

Llama 2 7B Chat Hf is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 2 7B Chat Hf by NousResearch — VRAM 13.5GB, 4K context

Name: Llama 2 7B Chat Hf
Author: NousResearch

Llama 2 7B Chat Hf is an open-source language model by NousResearch. Features: 7b LLM, VRAM: 13.5GB, Context: 4K, LLM Explorer Score: 0.13.

Deploy:azure En Facebook Llama Llama2 Meta Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/NousResearch/Llama-2-7b-chat-hf

Llama 2 7B Chat Hf Parameters and Internals

Model Type

text generation, dialogue

Use Cases

Areas:

Commercial use, Research use

Limitations:

Use in languages other than English, Use in violation of applicable laws or regulations

Additional Notes

Llama 2 models use Grouped-Query Attention (GQA) for improved inference scalability.

Supported Languages

English (proficient)

Training Details

Data Sources:

*A new mix of publicly available online data*

Data Volume:

2 trillion tokens

Methodology:

Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)

Context Length:

4000

Hardware Used:

Meta's Research Super Cluster, A100-80GB

Model Architecture:

Auto-regressive language model with transformer architecture

Responsible Ai Considerations

Fairness:

Testing conducted to date has been in English and cannot cover all scenarios.

Transparency:

Developers should perform safety testing and tuning tailored to their specific applications.

Accountability:

Restrictions on use to prevent infringement of laws and regulations.

Mitigation Strategies:

Align to human preferences for helpfulness and safety.

Input Output

Input Format:

Text

Accepted Modalities:

text

Output Format:

Text

Performance Tips:

To get the expected features and performance, a specific formatting needs to be followed, including `INST` and `<>` tags, `BOS` and `EOS` tokens, and whitespaces/breaklines.

LLM Name	Llama 2 7B Chat Hf
Repository 🤗	https://huggingface.co/NousResearch/Llama-2-7b-chat-hf
Model Size	7b
Required VRAM	13.5 GB
Updated	2026-07-20
Maintainer	NousResearch
Model Type	llama
Model Files	10.0 GB: 1-of-2 3.5 GB: 2-of-2 9.9 GB: 1-of-3 9.9 GB: 2-of-3 7.2 GB: 3-of-3
Supported Languages	en
Model Architecture	LlamaForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0.dev0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Llama 2 7B Chat Hf 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

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Note: green Score (e.g. "73.2") means that the model is better than NousResearch/Llama-2-7b-chat-hf.