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

Llama 2 7B Chat AWQ requires approximately 3.9 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 AWQ and how large is it?

Llama 2 7B Chat AWQ is developed by TheBloke, 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 AWQ?

Llama 2 7B Chat AWQ 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 AWQ by TheBloke — VRAM 3.9GB, 4K context

Name: Llama 2 7B Chat AWQ
Author: TheBloke

Llama 2 7B Chat AWQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 4K, License: llama2, Quantized, LLM Explorer Score: 0.1.

Arxiv:2307.09288 4-bit Awq Base model:meta-llama/llama-2-... Base model:quantized:meta-llam... Deploy:azure En Facebook Llama Llama2 Meta Pytorch Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Llama-2-7B-Chat-AWQ

Llama 2 7B Chat AWQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

Commercial applications, Research

Applications:

Assistant-like chat, Natural language generation

Primary Use Cases:

Dialogue optimization, Prompt-based text generation

Limitations:

English only, Not suitable for illegal uses

Considerations:

Developers should adhere to licensing agreements and perform additional safety testing.

Additional Notes

Model achieved lower emissions with Meta's sustainability program.

Supported Languages

en (High proficiency)

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:

4096

Training Time:

Between January 2023 and July 2023

Hardware Used:

A100-80GB GPUs

Model Architecture:

Transformer architecture

Safety Evaluation

Methodologies:

Internal evaluations

Findings:

Fine-tuned Llama-2-Chat models have 0% Toxigen

Risk Categories:

Misinformation, Bias

Ethical Considerations:

This model may produce inaccurate, biased or objectionable responses.

Responsible Ai Considerations

Fairness:

Conducted safe testing in English.

Transparency:

Usage requires adherence to licensing agreements.

Accountability:

Meta is accountable for the open release.

Mitigation Strategies:

Recommendations for developers to perform safety testing and tuning tailored to specific applications.

Input Output

Input Format:

[INST] <> {prompt} [/INST]

Accepted Modalities:

text

Output Format:

Text

Performance Tips:

Avoid non-factual or biased prompts for safety and accuracy.

Release Notes

Version:

Date:

July 2023

Notes:

Initial release with enhanced safety and performance benchmarks.

LLM Name	Llama 2 7B Chat AWQ
Repository 🤗	https://huggingface.co/TheBloke/Llama-2-7B-Chat-AWQ
Model Name	Llama 2 7B Chat
Model Creator	Meta Llama 2
Base Model(s)	Llama 2 7B Chat Hf meta-llama/Llama-2-7b-chat-hf
Model Size	7b
Required VRAM	3.9 GB
Updated	2026-07-17
Maintainer	TheBloke
Model Type	llama
Model Files	3.9 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.32.0.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 AWQ 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 Llama 2 7B Chat AWQ

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Smaugv0.1 AWQ	195K / 19.3 GB	9	1
Yarn Llama 2 7B 64K AWQ	64K / 3.9 GB	14	0
Calm2 7B Chat AWQ	32K / 4.4 GB	9	1
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... SWE Llama 7B Updated 4bit AWQ	16K / 3.9 GB	5	0
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CodeLlama 7B Instruct AWQ	16K / 3.9 GB	278	4
Pandalyst 7B V1.1 AWQ	16K / 3.9 GB	11	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Llama-2-7B-Chat-AWQ.