What are the hardware requirements for Qwen2.5 Taiwan 3B Instruct?

Qwen2.5 Taiwan 3B Instruct 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 Taiwan 3B Instruct and how large is it?

Qwen2.5 Taiwan 3B Instruct is developed by benchang1110, 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 Taiwan 3B Instruct?

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

Qwen2.5 Taiwan 3B Instruct by benchang1110 — VRAM 6.8GB, 32K context

Name: Qwen2.5 Taiwan 3B Instruct
Author: benchang1110

Qwen2.5 Taiwan 3B Instruct is an open-source language model by benchang1110. Features: 3b LLM, VRAM: 6.8GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.16.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-3b-ins... Conversational Dataset:lianghsun/tw-instruct-... Dataset:zake7749/kyara-chinese... En Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/benchang1110/Qwen2.5-Taiwan-3B-Instruct

Qwen2.5 Taiwan 3B Instruct Parameters and Internals

LLM Name	Qwen2.5 Taiwan 3B Instruct
Repository 🤗	https://huggingface.co/benchang1110/Qwen2.5-Taiwan-3B-Instruct
Base Model(s)	Qwen/Qwen2.5-3B-Instruct Qwen/Qwen2.5-3B-Instruct
Model Size	3b
Required VRAM	6.8 GB
Updated	2026-07-20
Maintainer	benchang1110
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 1.8 GB: 2-of-2
Supported Languages	zh en
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 Taiwan 3B 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

Best Alternatives to Qwen2.5 Taiwan 3B Instruct

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
... Instruct Sheldon RLVR Math V1	32K / 6.2 GB	876	0
Zen Ingress 1 3B Sft Merged	32K / 6.2 GB	738	1
EVOKE ALFWorld 3B	32K / 6.2 GB	247	1
Security Copilot Qwen2.5 3B	32K / 6.2 GB	403	0

Note: green Score (e.g. "73.2") means that the model is better than benchang1110/Qwen2.5-Taiwan-3B-Instruct.