What are the hardware requirements for Qwen2 7B?

Qwen2 7B requires approximately 15.4 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2 7B and how large is it?

Qwen2 7B 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.

How does Qwen2 7B perform on standard benchmarks?

Qwen2 7B has the following published scores: MMLU 70.45, LMSYS ELO 1404. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen2 7B by Qwen — VRAM 15.4GB, 128K context

Name: Qwen2 7B
Author: Qwen

Qwen2 7B is an open-source language model by Qwen. Features: 7b LLM, VRAM: 15.4GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.42, ELO: 1404, Arc: 59.7, HellaSwag: 79.8, MMLU: 70.5, GSM8K: 72.9.

Conversational Deploy:azure Deploy:sagemaker En Endpoints compatible Eval-results Pretrained Qwen2 Region:us Safetensors Sharded Tensorflow

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

Qwen2 7B Benchmarks

LMSys ELO 1404 vs 1272 (so35) 10.4%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen2 7B Parameters and Internals

Model Type

text generation

Use Cases

Areas:

research, commercial applications

Primary Use Cases:

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

Supported Languages

English (proficient), Chinese (proficient), Multilingual (varied proficiency)

Training Details

Methodology:

Transformer architecture with SwiGLU activation, attention QKV bias, group query attention.

Model Architecture:

Transformer

Input Output

Accepted Modalities:

text

Performance Tips:

It is suggested to not use base language models for text generation directly. Instead, apply post-training techniques like SFT, RLHF, continued pretraining on this model.

LLM Name	Qwen2 7B
Repository 🤗	https://huggingface.co/Qwen/Qwen2-7B
Model Size	7b
Required VRAM	15.4 GB
Updated	2026-08-06
Maintainer	Qwen
Model Type	qwen2
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	131072
Model Max Length	131072
Transformers Version	4.37.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2 7B 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

Model	Likes	Downloads	VRAM
...lphin 2.9.2 Qwen2 7B Bpw6 EXL2	1	7	6 GB
Samantha Qwen2 7B AWQ	0	10	5 GB

Best Alternatives to Qwen2 7B

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Preview	986K / 15.2 GB	10	0
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Hush Qwen2.5 7B V1.2	986K / 15.2 GB	4	1
Hush Qwen2.5 7B V1.1	986K / 15.2 GB	5	1
Hush Qwen2.5 7B V1.4	986K / 15.2 GB	8	1
Hush Qwen2.5 7B Preview	986K / 15.2 GB	5	0
Hush Qwen2.5 7B V1.3	986K / 15.2 GB	10	2
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen 2.5 7B Exp Sce	986K / 15.2 GB	10	2
Qwen2.5 7B MixStock V0.1	986K / 15.2 GB	6	3