What are the hardware requirements for Qwen3 30B A3B GGUF?

Qwen3 30B A3B GGUF requires approximately 9 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 30B A3B GGUF and how large is it?

Qwen3 30B A3B GGUF is developed by unsloth, a model with 30b 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 30B A3B GGUF?

Qwen3 30B A3B GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 30B A3B GGUF by unsloth — VRAM 9GB, 40K context

Name: Qwen3 30B A3B GGUF
Author: unsloth

Qwen3 30B A3B GGUF is an open-source language model by unsloth. Features: 30b LLM, VRAM: 9GB, Context: 40K, License: apache-2.0, Quantized, LLM Explorer Score: 0.26.

Arxiv:2309.00071 Base model:quantized:qwen/qwen... Base model:qwen/qwen3-30b-a3b Conversational En Endpoints compatible Gguf Imatrix Q2 Quantized Qwen Qwen3 Qwen3 moe Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen3-30B-A3B-GGUF

Qwen3 30B A3B GGUF Parameters and Internals

LLM Name	Qwen3 30B A3B GGUF
Repository 🤗	https://huggingface.co/unsloth/Qwen3-30B-A3B-GGUF
Base Model(s)	Qwen3 30B A3B Qwen/Qwen3-30B-A3B
Model Size	30b
Required VRAM	9 GB
Updated	2026-07-23
Maintainer	unsloth
Model Type	qwen3_moe
Model Files	17.3 GB 16.4 GB 11.3 GB 11.3 GB 14.7 GB 13.3 GB 17.4 GB 19.2 GB 18.6 GB 17.5 GB 21.7 GB 21.1 GB 25.1 GB 32.5 GB 9.7 GB 9.0 GB 10.9 GB 10.4 GB 12.9 GB 11.8 GB 13.8 GB 17.7 GB 21.7 GB 26.3 GB 36.0 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|q2\|q4_k\|q5_k
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.51.3
Vocabulary Size	151936
Torch Data Type	bfloat16

Rank the Qwen3 30B A3B GGUF 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 Qwen3 30B A3B GGUF

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3 30B A3B 128K GGUF	128K / 9 GB	2730	61
...en3 30B A3B Instruct 2507 4bit	256K / 17.2 GB	83766	12
...30B A3B Instruct 2507 MLX 4bit	256K / 17.2 GB	24652	8
...30B A3B Instruct 2507 MLX 8bit	256K / 32.5 GB	24655	3
...n3 Coder 30B A3B Instruct 4bit	256K / 17.2 GB	7252	33
...r 30B A3B Instruct 4bit Dwq V2	256K / 17.2 GB	1342	10
...n3 Coder 30B A3B Instruct 8bit	256K / 32.5 GB	1277	7
...oder 30B A3B Instruct 4bit DWQ	256K / 17.2 GB	644	5
...30B A3B Thinking 2507 MLX 4bit	256K / 17.2 GB	576	1
...en3 30B A3B Thinking 2507 4bit	256K / 17.2 GB	232	4

Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen3-30B-A3B-GGUF.