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

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

Vicuna 7B V1.5 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 Vicuna 7B V1.5 AWQ?

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

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

Vicuna 7B V1.5 AWQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 4K, License: llama2, Quantized, LLM Explorer Score: 0.09.

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

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

Vicuna 7B V1.5 AWQ Parameters and Internals

Model Type

llama

Additional Notes

The model uses AWQ, an efficient, accurate, and fast low-bit weight quantization, supporting 4-bit quantization. This results in faster inference and the ability to use smaller GPUs for deployment.

Training Details

Data Sources:

ShareGPT

Methodology:

Finetuned with supervised instruction on user-shared conversations.

Context Length:

4096

Model Architecture:

Transformer

Input Output

Input Format:

The assistant gives helpful, detailed, and polite answers to the user''s questions. USER: {prompt} ASSISTANT:

LLM Name	Vicuna 7B V1.5 AWQ
Repository 🤗	https://huggingface.co/TheBloke/vicuna-7B-v1.5-AWQ
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	2026-07-31
Maintainer	TheBloke
Model Type	llama
Model Files	3.9 GB
AWQ Quantization	Yes
Quantization Type	awq
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 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 Vicuna 7B V1.5 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
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
Llama 2 7B 32K Instruct AWQ	32K / 3.9 GB	3	2
... SWE Llama 7B Updated 4bit AWQ	16K / 3.9 GB	5	0
Pandalyst 7B V1.2 AWQ	16K / 3.9 GB	6	1
Tora Code 7B V1.0 AWQ	16K / 3.9 GB	5	0
...eechless Tora Code 7B V1.0 AWQ	16K / 3.9 GB	6	1
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/vicuna-7B-v1.5-AWQ.