What are the hardware requirements for Qwen2.5 3B Instruct SFT In WebShop?

Qwen2.5 3B Instruct SFT In WebShop requires approximately 6.8 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 3B Instruct SFT In WebShop and how large is it?

Qwen2.5 3B Instruct SFT In WebShop is developed by ZuoHaotong, 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 3B Instruct SFT In WebShop?

Qwen2.5 3B Instruct SFT In WebShop is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 3B Instruct SFT In WebShop by ZuoHaotong — VRAM 6.8GB, 32K context

Name: Qwen2.5 3B Instruct SFT In WebShop
Author: ZuoHaotong

Qwen2.5 3B Instruct SFT In WebShop is an open-source language model by ZuoHaotong. Features: 3b LLM, VRAM: 6.8GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.32.

Agent Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-3b-ins... Conversational En Endpoints compatible Instruct Qwen2 Qwen2.5 Reasoning Region:us Safetensors Sft Sharded Tensorflow Tool-use Webshop Zh

Model Card on HF 🤗: https://huggingface.co/ZuoHaotong/Qwen2.5-3B-Instruct-SFT-in-WebShop

Qwen2.5 3B Instruct SFT In WebShop Parameters and Internals

LLM Name	Qwen2.5 3B Instruct SFT In WebShop
Repository 🤗	https://huggingface.co/ZuoHaotong/Qwen2.5-3B-Instruct-SFT-in-WebShop
Base Model(s)	Qwen/Qwen2.5-3B-Instruct Qwen/Qwen2.5-3B-Instruct
Model Size	3b
Required VRAM	6.8 GB
Updated	2026-08-22
Maintainer	ZuoHaotong
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 1.8 GB: 2-of-2
Supported Languages	en zh
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.48.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 3B Instruct SFT In WebShop 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

Best Alternatives to Qwen2.5 3B Instruct SFT In WebShop

Best Alternatives	Context / RAM	Downloads	Likes
VibeThinker 3B	128K / 6.2 GB	52745	806
VibeThinker 3B	128K / 6.2 GB	361	0
Saba2 3B	128K / 6.2 GB	6	0
Tessa T1 3B	117K / 6.2 GB	10	5
UIGEN T1.5 3B	117K / 6.2 GB	7	1
Qwen2.5 3B Instruct	32K / 6.2 GB	5889234	545
SmallThinker 3B Preview	32K / 6.8 GB	30529	412
Qwen2.5 3B Haizi	32K / 6.2 GB	74	0
...n2.5 3B FinCode Reasoning Full	32K / 6.2 GB	12	1
ResearchMate Qwen2.5 3B	32K / 6.2 GB	66	2

Note: green Score (e.g. "73.2") means that the model is better than ZuoHaotong/Qwen2.5-3B-Instruct-SFT-in-WebShop.