What are the hardware requirements for Qwen3 4B Instruct 2507 Unsloth Bnb 4bit?

Qwen3 4B Instruct 2507 Unsloth Bnb 4bit requires approximately 3.5 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 Qwen3 4B Instruct 2507 Unsloth Bnb 4bit and how large is it?

Qwen3 4B Instruct 2507 Unsloth Bnb 4bit is developed by unsloth, a model with 4b 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 Qwen3 4B Instruct 2507 Unsloth Bnb 4bit?

Qwen3 4B Instruct 2507 Unsloth Bnb 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 4B Instruct 2507 Unsloth Bnb 4bit by unsloth — VRAM 3.5GB, 256K context

Name: Qwen3 4B Instruct 2507 Unsloth Bnb 4bit
Author: unsloth

Qwen3 4B Instruct 2507 Unsloth Bnb 4bit is an open-source language model by unsloth. Features: 4b LLM, VRAM: 3.5GB, Context: 256K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.27.

Arxiv:2505.09388 4-bit 4bit Base model:quantized:qwen/qwen... Base model:qwen/qwen3-4b-instr... Bitsandbytes Conversational Endpoints compatible Instruct Quantized Qwen3 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit

Qwen3 4B Instruct 2507 Unsloth Bnb 4bit Parameters and Internals

LLM Name	Qwen3 4B Instruct 2507 Unsloth Bnb 4bit
Repository 🤗	https://huggingface.co/unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit
Base Model(s)	Qwen3 4B Instruct 2507 Qwen/Qwen3-4B-Instruct-2507
Model Size	4b
Required VRAM	3.5 GB
Updated	2026-09-12
Maintainer	unsloth
Model Type	qwen3
Instruction-Based	Yes
Model Files	3.5 GB
Quantization Type	4bit
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.55.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 4B Instruct 2507 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 Qwen3 4B Instruct 2507 Unsloth Bnb 4bit

Model	Likes	Downloads	VRAM
Agent 4b	0	16	8 GB
Fact Extractor Dev 1b	0	20	8 GB

Best Alternatives to Qwen3 4B Instruct 2507 Unsloth Bnb 4bit

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3 4b Merged Txt	256K / 8.1 GB	535	0
Qwen3 4B Instruct 2507 4bit	256K / 2.3 GB	40955	11
...wen 3 4b Mythos Finetune 16bit	256K / 8.1 GB	92	0
Qwen3 4B INST Code	256K / 8.1 GB	20	0
Qwen3 4B INST Math	256K / 8.1 GB	23	0
...Instruct Haiku 4.5 Merged FP16	256K / 8.1 GB	16	1
Agent 4b	256K / 8.1 GB	16	0
...wen3 4B Instruct 2507 Bnb 4bit	256K / 2.6 GB	6833	5
...B Z Image Engineer V2 6bit MLX	256K / 3.3 GB	605	7
Jan V3 4B Base Instruct 4bit	256K / 2.3 GB	279	2

Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit.