What are the hardware requirements for Qwen3 30B A3B Thinking 2507?

Qwen3 30B A3B Thinking 2507 requires approximately 61.1 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 30B A3B Thinking 2507 and how large is it?

Qwen3 30B A3B Thinking 2507 is developed by Qwen, 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 Thinking 2507?

Qwen3 30B A3B Thinking 2507 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 30B A3B Thinking 2507 by Qwen — VRAM 61.1GB, 256K context

Name: Qwen3 30B A3B Thinking 2507
Author: Qwen

Qwen3 30B A3B Thinking 2507 is an open-source language model by Qwen. Features: 30b LLM, VRAM: 61.1GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.29.

Arxiv:2402.17463 Arxiv:2404.06654 Arxiv:2407.02490 Arxiv:2501.15383 Arxiv:2505.09388 Conversational Deploy:azure Endpoints compatible Eval-results Qwen3 moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507

Qwen3 30B A3B Thinking 2507 Parameters and Internals

LLM Name	Qwen3 30B A3B Thinking 2507
Repository 🤗	https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507
Model Size	30b
Required VRAM	61.1 GB
Updated	2026-06-08
Maintainer	Qwen
Model Type	qwen3_moe
Model Files	4.0 GB: 1-of-16 4.0 GB: 2-of-16 4.0 GB: 3-of-16 4.0 GB: 4-of-16 4.0 GB: 5-of-16 4.0 GB: 6-of-16 4.0 GB: 7-of-16 4.0 GB: 8-of-16 4.0 GB: 9-of-16 4.0 GB: 10-of-16 4.0 GB: 11-of-16 4.0 GB: 12-of-16 4.0 GB: 13-of-16 4.0 GB: 14-of-16 4.0 GB: 15-of-16 1.1 GB: 16-of-16
Model Architecture	Qwen3MoeForCausalLM
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 30B A3B Thinking 2507 capabilities

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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 30B A3B Thinking 2507

Model	Likes	Downloads	VRAM
...30B A3B Thinking 2507 AWQ 4bit	15	306994	18 GB
...30B A3B Thinking 2507 AWQ 4bit	8	67401	16 GB
...wen3 30B A3B Thinking 2507 AWQ	6	4825	16 GB
...30B A3B Thinking 2507 MLX 4bit	1	576	17 GB
...en3 30B A3B Thinking 2507 4bit	4	232	17 GB

Best Alternatives to Qwen3 30B A3B Thinking 2507

Best Alternatives	Context / RAM	Downloads	Likes
...LL MASTER CODER M 1million Ctx	1024K / 84.8 GB	195	11
... 42B A3B Thinking Total Recall	986K / 84.8 GB	26	0
Qwen3 30B A3B YOYO V3	986K / 61.1 GB	11	7
...07 YOYO2 TOTAL RECALL Instruct	986K / 84.8 GB	27	1
...07 YOYO2 TOTAL RECALL Instruct	986K / 106 GB	20	0
Qwen3 30B A3B YOYO V2	986K / 61.1 GB	19	4
Qwen3 Coder 30B A3B Instruct	256K / 61.1 GB	1746771	1168
Qwen3 30B A3B Instruct 2507	256K / 61.1 GB	3937	13
Qwen3 30B A3B Instruct 2507	256K / 61.1 GB	1903736	824
...en3 Coder 30B A3B Instruct FP8	256K / 31.2 GB	1556690	191

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen3-30B-A3B-Thinking-2507.