What are the hardware requirements for Vigogne 2 7B Instruct GGML?

Vigogne 2 7B Instruct 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 Vigogne 2 7B Instruct GGML and how large is it?

Vigogne 2 7B Instruct 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 Vigogne 2 7B Instruct GGML?

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

Vigogne 2 7B Instruct GGML by TheBloke — VRAM 2.9GB

Name: Vigogne 2 7B Instruct GGML
Author: TheBloke

Vigogne 2 7B Instruct GGML is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 2.9GB, License: llama2, Quantized, Instruction-Based, LLM Explorer Score: 0.08.

Base model:bofenghuang/vigogne... Base model:finetune:bofenghuan... Fr Ggml Instruct Llama Llama2 Quantized Region:us

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

Vigogne 2 7B Instruct GGML Parameters and Internals

Model Type

LLM, Instruct

Additional Notes

Vigogne is still under development, and there are many limitations that have to be addressed. Please note that it is possible that the model generates harmful or biased content, incorrect information or generally unhelpful answers.

Supported Languages

French (high)

LLM Name	Vigogne 2 7B Instruct GGML
Repository 🤗	https://huggingface.co/TheBloke/Vigogne-2-7B-Instruct-GGML
Model Name	Vigogne 2 7B Instruct
Model Creator	bofenghuang
Base Model(s)	Vigogne 2 7B Instruct bofenghuang/vigogne-2-7b-instruct
Model Size	7b
Required VRAM	2.9 GB
Updated	2026-06-10
Maintainer	TheBloke
Model Type	llama
Instruction-Based	Yes
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 4.7 GB 5.1 GB 4.8 GB 4.7 GB 5.5 GB 7.1 GB
Supported Languages	fr
GGML Quantization	Yes
Quantization Type	ggml
Model Architecture	AutoModel
License	llama2

Rank the Vigogne 2 7B Instruct 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

Best Alternatives to Vigogne 2 7B Instruct GGML

Best Alternatives	Context / RAM	Downloads	Likes
CodeLlama 7B Instruct GGML	0K / 3 GB	10	20
Llama 2 7B 32K Instruct GGML	0K / 2.9 GB	7	8
Falcon 7B Instruct GGML	0K / 4.1 GB	12	40
Redpajama 7B GGML	0K / 3.9 GB	9	3
MPT 7B Instruct GGML	0K / 3.7 GB	64	30
Mpt 7B GGML	0K / 3.7 GB	21	46
Badqubits Mistral 7B V03 Ft	0K / 0.2 GB	28	1
Poetes Mistral 7B Lora	0K / 0.2 GB	25	1
Qwen Phoenix Lora	0K / 0.2 GB	17	1
Forma Uiux Auditor	0K / 0.2 GB	25	1

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