What are the hardware requirements for Qwen2.5 4B?

Qwen2.5 4B requires approximately 8.4 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 Qwen2.5 4B and how large is it?

Qwen2.5 4B is developed by qingy2024, a model with 3b 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 Qwen2.5 4B?

Qwen2.5 4B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 4B by qingy2024 — VRAM 8.4GB, 32K context

Name: Qwen2.5 4B
Author: qingy2024

Qwen2.5 4B is an open-source language model by qingy2024. Features: 3b LLM, VRAM: 8.4GB, Context: 32K, Merged, LLM Explorer Score: 0.2.

Merged Model Ara Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-3b Conversational Deu Endpoints compatible Eng Fra Ita Jpn Kor Por Qwen2 Region:us Rus Safetensors Sharded Spa Tensorflow Tha Vie Zho

Model Card on HF 🤗: https://huggingface.co/qingy2024/Qwen2.5-4B

Qwen2.5 4B Parameters and Internals

LLM Name	Qwen2.5 4B
Repository 🤗	https://huggingface.co/qingy2024/Qwen2.5-4B
Base Model(s)	Qwen/Qwen2.5-3B Qwen/Qwen2.5-3B
Merged Model	Yes
Model Size	3b
Required VRAM	8.4 GB
Updated	2026-07-07
Maintainer	qingy2024
Model Type	qwen2
Model Files	5.0 GB: 1-of-2 3.4 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 4B 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

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Note: green Score (e.g. "73.2") means that the model is better than qingy2024/Qwen2.5-4B.