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

Llama 2 7B Chat GGML requires approximately 2.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Llama 2 7B Chat GGML 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 GGML?

Llama 2 7B Chat GGML 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 GGML by TheBloke — VRAM 2.9GB

Name: Llama 2 7B Chat GGML
Author: TheBloke

Llama 2 7B Chat GGML is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 2.9GB, License: other, Quantized, LLM Explorer Score: 0.1.

Arxiv:2307.09288 Base model:finetune:meta-llama... Base model:meta-llama/llama-2-... En Facebook Ggml Llama Llama2 Meta Pytorch Quantized Region:us

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

Llama 2 7B Chat GGML Parameters and Internals

Model Type

llama

Use Cases

Primary Use Cases:

Assistant-like chat

Limitations:

Use in languages other than English, Generating objectionable or biased content

Considerations:

Developers should ensure safety testing and tuning before deploying applications.

Additional Notes

Llama 2's potential outputs cannot be predicted. Developers need to perform application-specific safety testing.

Training Details

Data Sources:

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:

A100-80GB GPUs

Model Architecture:

Auto-regressive transformer

Responsible Ai Considerations

Transparency:

The model is fine-tuned to align with human preferences for safety and helpfulness.

Mitigation Strategies:

Follow responsible use guidelines to prevent misuse.

Input Output

Input Format:

Text input with specific formatting using tags like INST and special tokens.

Accepted Modalities:

text

Output Format:

Text generation

Performance Tips:

Output relies on using specific formatting and tokens for optimal results.

LLM Name	Llama 2 7B Chat GGML
Repository 🤗	https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML
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	2.9 GB
Updated	2026-07-10
Maintainer	TheBloke
Model Type	llama
Model Files	2.9 GB 3.6 GB 3.3 GB 3.0 GB 3.8 GB 4.2 GB 4.1 GB 3.8 GB 4.6 GB 5.1 GB 4.8 GB 4.7 GB 5.5 GB 7.2 GB
Supported Languages	en
GGML Quantization	Yes
Quantization Type	ggml
Model Architecture	AutoModel
License	other

Rank the Llama 2 7B Chat GGML 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

Quantized Models of the Llama 2 7B Chat GGML

Model	Likes	Downloads	VRAM
Llama 2 GGML Medical Chatbot	45	14	0 GB

Best Alternatives to Llama 2 7B Chat GGML

Best Alternatives	Context / RAM	Downloads	Likes
Llama 2 GGML Medical Chatbot	0K / GB	14	45
Llama 2 7B GGML	0K / 2.9 GB	147	219
Yarn Llama 2 7B 128K GGML	0K / 2.9 GB	3	6
Yarn Llama 2 7B 64K GGML	0K / 2.9 GB	5	3
CodeLlama 7B GGML	0K / 3 GB	10	27
CodeLlama 7B Python GGML	0K / 2.9 GB	6	24
CodeLlama 7B Instruct GGML	0K / 3 GB	10	20
Airoboros L2 7B 2.1 GGML	0K / 2.9 GB	5	1
Zarafusionex 1.1 L2 7B GGML	0K / 2.9 GB	6	2
EDGE 0 7B GGML	0K / 2.9 GB	2	1