What are the hardware requirements for Qwen2.5 3B Instruct Unsloth Bnb 4bit?

Qwen2.5 3B Instruct Unsloth Bnb 4bit requires approximately 2.4 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 3B Instruct Unsloth Bnb 4bit and how large is it?

Qwen2.5 3B Instruct Unsloth Bnb 4bit is developed by unsloth, 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 Unsloth Bnb 4bit?

Qwen2.5 3B Instruct Unsloth Bnb 4bit 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 Unsloth Bnb 4bit by unsloth — VRAM 2.4GB, 32K context

Name: Qwen2.5 3B Instruct Unsloth Bnb 4bit
Author: unsloth

Qwen2.5 3B Instruct Unsloth Bnb 4bit is an open-source language model by unsloth. Features: 3b LLM, VRAM: 2.4GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.23.

Arxiv:2407.10671 4-bit 4bit Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-3b-ins... Bitsandbytes Conversational Deploy:azure En Endpoints compatible Instruct Quantized Qwen Qwen2 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen2.5-3B-Instruct-unsloth-bnb-4bit

Qwen2.5 3B Instruct Unsloth Bnb 4bit Parameters and Internals

LLM Name	Qwen2.5 3B Instruct Unsloth Bnb 4bit
Repository 🤗	https://huggingface.co/unsloth/Qwen2.5-3B-Instruct-unsloth-bnb-4bit
Base Model(s)	Qwen/Qwen2.5-3B-Instruct Qwen/Qwen2.5-3B-Instruct
Model Size	3b
Required VRAM	2.4 GB
Updated	2026-10-21
Maintainer	unsloth
Model Type	qwen2
Instruction-Based	Yes
Model Files	2.4 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 3B Instruct Unsloth Bnb 4bit 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 Qwen2.5 3B Instruct Unsloth Bnb 4bit

Model	Likes	Downloads	VRAM
Delivery Qwen2.5 7B Driver	1	274	6 GB
Qwen2.5 3B Indonesian Sft	0	433	6 GB
Qwen2.5 3B Legal Id Sft	0	33	6 GB

Best Alternatives to Qwen2.5 3B Instruct Unsloth Bnb 4bit

Best Alternatives	Context / RAM	Downloads	Likes
VibeThinker 3B 8bit	128K / 3.3 GB	740	3
VibeThinker 3B 4bit	128K / 1.7 GB	122	1
Delivery Qwen2.5 7B Driver	32K / 6.2 GB	274	1
Qwen2.5 3B Indonesian Sft	32K / 6.2 GB	433	0
Legal Qwen SFT Indo	32K / 6.2 GB	499	0
Qwen2.5 3B Legal Id Sft	32K / 6.2 GB	300	0
Qwen2.5 3B Legal Id Sft	32K / 6.2 GB	33	0
...truct Bnb 4bit Legal Assistant	32K / 6.2 GB	61	0
Sft Qwen25 3B Run1	32K / 6.2 GB	60	0
Qwen2.5 3B Legal Sft	32K / 6.2 GB	269	0

Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen2.5-3B-Instruct-unsloth-bnb-4bit.