What are the hardware requirements for Qwen2 7B Instruct?

Qwen2 7B Instruct requires approximately 15.4 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 Qwen2 7B Instruct and how large is it?

Qwen2 7B Instruct is developed by Qwen, 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 Qwen2 7B Instruct?

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

Qwen2 7B Instruct by Qwen — VRAM 15.4GB, 32K context

Name: Qwen2 7B Instruct
Rating: 4 (3 reviews)
Author: Qwen

Qwen2 7B Instruct is an open-source language model by Qwen. Features: 7b LLM, VRAM: 15.4GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.32.

Arxiv:2309.00071 Base model:finetune:qwen/qwen2... Base model:qwen/qwen2-7b Chat Conversational Deploy:sagemaker En Endpoints compatible Eval-results Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2-7B-Instruct

Qwen2 7B Instruct Parameters and Internals

Model Type

decoder, language model

Use Cases

Areas:

research, text generation, multilingual processing, coding

Primary Use Cases:

language understanding, language generation, multilingual capability, coding, mathematics, reasoning

Considerations:

Ensure performance on shorter texts may be impacted when rope_scaling is configured for long texts.

Supported Languages

en (English)

Training Details

Data Volume:

large amount of data

Methodology:

supervised finetuning and direct preference optimization

Context Length:

131072

Model Architecture:

Transformer with SwiGLU activation, attention QKV bias, and group query attention

Input Output

Accepted Modalities:

text

Performance Tips:

For handling long texts, enable YARN configuration in settings.

LLM Name	Qwen2 7B Instruct
Repository 🤗	https://huggingface.co/Qwen/Qwen2-7B-Instruct
Base Model(s)	Qwen2 7B Qwen/Qwen2-7B
Model Size	7b
Required VRAM	15.4 GB
Updated	2026-07-31
Maintainer	Qwen
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.0 GB: 1-of-4 3.9 GB: 2-of-4 3.9 GB: 3-of-4 3.6 GB: 4-of-4
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2 7B Instruct 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 Qwen2 7B Instruct

Model	Likes	Downloads	VRAM
Qwen2 7B Instruct GGUF	10	56414	1 GB
Qwen2 7B Instruct AWQ	23	20200	5 GB
Qwen2 7B Instruct GPTQ Int8	17	1646	8 GB
Qwen2 7B Instruct GPTQ Int4	28	546	5 GB
Qwen2 7B Instruct GGUF	1	192	3 GB
Qwen2 7B Instruct GGUF	0	121	3 GB

Best Alternatives to Qwen2 7B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Rewnozom	986K / 30.5 GB	742	1
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

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