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

Qwen3 4B Instruct 2507 requires approximately 8.1 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 and how large is it?

Qwen3 4B Instruct 2507 is developed by Qwen, 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?

Qwen3 4B Instruct 2507 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 by Qwen — VRAM 8.1GB, 256K context

Name: Qwen3 4B Instruct 2507
Rating: 3 (1 reviews)
Author: Qwen

Qwen3 4B Instruct 2507 is an open-source language model by Qwen. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.36.

Arxiv:2505.09388 Conversational Deploy:azure Deploy:sagemaker Endpoints compatible Eval-results Instruct Qwen3 Region:us Safetensors Sharded Tensorflow

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

Qwen3 4B Instruct 2507 Parameters and Internals

LLM Name	Qwen3 4B Instruct 2507
Repository 🤗	https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-08-07
Maintainer	Qwen
Model Type	qwen3
Instruction-Based	Yes
Model Files	4.0 GB: 1-of-3 4.0 GB: 2-of-3 0.1 GB: 3-of-3
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.51.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 4B Instruct 2507 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

Model	Likes	Downloads	VRAM
...Instruct 2507 Unsloth Bnb 4bit	17	116366	3 GB
Qwen3 4B Instruct 2507 4bit	11	40955	2 GB
...Instruct Haiku 4.5 Merged FP16	1	16	8 GB
...wen3 4B Toolcalling Gguf Codex	55	2613	4 GB
...wen3 4B Instruct 2507 Bnb 4bit	5	6833	2 GB
...B Toolcall Gguf Llamacpp Codex	9	1304	4 GB
...4B Instruct 2507 4bit DWQ 2510	2	407	2 GB
Qwen3 4B Instruct 2507 8bit	4	594	4 GB
Qwen3 4B Instruct 2507 6bit	1	66	3 GB

Best Alternatives to Qwen3 4B Instruct 2507

Best Alternatives	Context / RAM	Downloads	Likes
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Fable Traces	256K / 8.1 GB	343	210
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Sft Prm	256K / 17.6 GB	602	0
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
...pt Full Qwen3 4b Instruct 2507	256K / 8 GB	365	1
Nexa AI 4B Instruct	256K / 8 GB	576	2
Neuron 4B Instruct	256K / 8.1 GB	313	1
Agents K1	256K / 8.8 GB	1098	28
FastContext 1.0 4B SFT	256K / 8.1 GB	273	18

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