What are the hardware requirements for Vi Qwen2 7B RAG?

Vi Qwen2 7B RAG requires approximately 15.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Vi Qwen2 7B RAG and how large is it?

Vi Qwen2 7B RAG is developed by AITeamVN, 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 Vi Qwen2 7B RAG?

Vi Qwen2 7B RAG is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Vi Qwen2 7B RAG by AITeamVN — VRAM 15.2GB, 32K context

Name: Vi Qwen2 7B RAG
Author: AITeamVN

Vi Qwen2 7B RAG is an open-source language model by AITeamVN. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.16.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2-7b-instr... Conversational Endpoints compatible Instruct Qwen2 Region:us Retrieval-augmented-generation Safetensors Sharded Tensorflow Vi

Model Card on HF 🤗: https://huggingface.co/AITeamVN/Vi-Qwen2-7B-RAG

Vi Qwen2 7B RAG Parameters and Internals

LLM Name	Vi Qwen2 7B RAG
Repository 🤗	https://huggingface.co/AITeamVN/Vi-Qwen2-7B-RAG
Base Model(s)	Qwen2 7B Instruct Qwen/Qwen2-7B-Instruct
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-08-01
Maintainer	AITeamVN
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Supported Languages	vi
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.43.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Vi Qwen2 7B RAG capabilities

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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 Vi Qwen2 7B RAG

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen2.5 7B RRP 1M	986K / 15.2 GB	5	6
Qwen2.5 7B CelestialHarmony 1M	986K / 14.8 GB	8	7
Q2.5 Instruct 1M Harmony	986K / 15.2 GB	4	2
Impish QWEN 7B 1M	986K / 15.2 GB	4	6
COCO 7B Instruct 1M	986K / 15.2 GB	9	4
Apollo 7B	986K / 15.2 GB	8	0
Graph R1 7B	986K / 15.3 GB	7	3
Qwen2.5 7B Sky R1 Mini	986K / 15.2 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than AITeamVN/Vi-Qwen2-7B-RAG.