What are the hardware requirements for Vicuna 7B V1.5 GPTQ?

Vicuna 7B V1.5 GPTQ 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 Vicuna 7B V1.5 GPTQ and how large is it?

Vicuna 7B V1.5 GPTQ 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 Vicuna 7B V1.5 GPTQ?

Vicuna 7B V1.5 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Vicuna 7B V1.5 GPTQ by TheBloke — VRAM 3.9GB, 4K context

Name: Vicuna 7B V1.5 GPTQ
Author: TheBloke

Vicuna 7B V1.5 GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 4K, License: llama2, Quantized, LLM Explorer Score: 0.08.

Arxiv:2306.05685 Arxiv:2307.09288 4-bit Base model:lmsys/vicuna-7b-v1.... Base model:quantized:lmsys/vic... Gptq Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/vicuna-7B-v1.5-GPTQ

Vicuna 7B V1.5 GPTQ Parameters and Internals

Model Type

auto-regressive language model, transformer architecture

Use Cases

Areas:

research on large language models, chatbots

Additional Notes

The model is positioned as a chat assistant with intended users being researchers and hobbyists in NLP, ML, and AI.

Training Details

Data Sources:

ShareGPT.com

Data Volume:

around 125K conversations

Methodology:

supervised instruction fine-tuning

Input Output

Input Format:

General prompting as a conversation between a user and an AI assistant.

Accepted Modalities:

text

Output Format:

Textual response from the AI assistant.

LLM Name	Vicuna 7B V1.5 GPTQ
Repository 🤗	https://huggingface.co/TheBloke/vicuna-7B-v1.5-GPTQ
Model Name	Vicuna 7B v1.5
Model Creator	lmsys
Base Model(s)	lmsys/vicuna-7b-v1.5 lmsys/vicuna-7b-v1.5
Model Size	7b
Required VRAM	3.9 GB
Updated	2026-08-07
Maintainer	TheBloke
Model Type	llama
Model Files	3.9 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0
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 Vicuna 7B V1.5 GPTQ 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 Vicuna 7B V1.5 GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Yarn Llama 2 7B 128K GPTQ	128K / 3.9 GB	8	7
Yarn Llama 2 7B 64K GPTQ	64K / 3.9 GB	10	1
... 7B 32K Instructions V4 Marlin	32K / 4.1 GB	8	0
Aixcoder 7B GPTQ	32K / 4.5 GB	4	1
Calm2 7B Chat GPTQ	32K / 4.4 GB	6	5
...Calm2 7B Chat GPTQ Calib Ja 1K	32K / 4.4 GB	4	5
Llama 2 7B 32K Instruct GPTQ	32K / 3.9 GB	49	27
Codebear 7B 4bit	16K / 3.9 GB	4	1
...a 7B Instruct GPTQ Calib Ja 1K	16K / 3.9 GB	6	0
Pandalyst 7B V1.2 GPTQ	16K / 3.9 GB	8	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/vicuna-7B-v1.5-GPTQ.