What are the hardware requirements for Qwen Image 2.1 PE T2I Pocket 2B?

Qwen Image 2.1 PE T2I Pocket 2B requires approximately 3.8 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen Image 2.1 PE T2I Pocket 2B and how large is it?

Qwen Image 2.1 PE T2I Pocket 2B is developed by ML-Intern-lab, a model with 2b 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 Qwen Image 2.1 PE T2I Pocket 2B?

Qwen Image 2.1 PE T2I Pocket 2B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen Image 2.1 PE T2I Pocket 2B by ML-Intern-lab — VRAM 3.8GB, 256K context

Name: Qwen Image 2.1 PE T2I Pocket 2B
Author: ML-Intern-lab

Qwen Image 2.1 PE T2I Pocket 2B is an open-source language model by ML-Intern-lab. Features: 2b LLM, VRAM: 3.8GB, Context: 256K, License: other, LLM Explorer Score: 0.34.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-2b Conversational Distillation Endpoints compatible Qwen3 5 text Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/ML-Intern-lab/Qwen-Image-2.1-PE-T2I-Pocket-2B

Qwen Image 2.1 PE T2I Pocket 2B Parameters and Internals

LLM Name	Qwen Image 2.1 PE T2I Pocket 2B
Repository 🤗	https://huggingface.co/ML-Intern-lab/Qwen-Image-2.1-PE-T2I-Pocket-2B
Base Model(s)	Qwen/Qwen3.5-2B Qwen/Qwen3.5-2B
Model Size	2b
Required VRAM	3.8 GB
Updated	2026-10-01
Maintainer	ML-Intern-lab
Model Type	qwen3_5_text
Model Files	3.8 GB 0.0 GB
Model Architecture	Qwen3_5ForCausalLM
License	other
Context Length	262144
Model Max Length	262144
Transformers Version	5.17.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwen Image 2.1 PE T2I Pocket 2B 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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