What are the hardware requirements for Qwen3 30B A3B YOYO V6?

Qwen3 30B A3B YOYO V6 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 YOYO V6 and how large is it?

Qwen3 30B A3B YOYO V6 is developed by YOYO-AI, 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 YOYO V6?

Qwen3 30B A3B YOYO V6 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 30B A3B YOYO V6 by YOYO-AI — VRAM 61.1GB, 256K context

Name: Qwen3 30B A3B YOYO V6
Author: YOYO-AI

Qwen3 30B A3B YOYO V6 is an open-source language model by YOYO-AI. Features: 30b LLM, VRAM: 61.1GB, Context: 256K, License: apache-2.0, Instruction-Based, Code Generating, LLM Explorer Score: 0.22.

Arxiv:2506.16506 Base model:merge:qwen/qwen3-30... Base model:merge:qwen/qwen3-30... Base model:merge:qwen/qwen3-30... Base model:merge:qwen/qwen3-co... Base model:qwen/qwen3-30b-a3b-... Base model:qwen/qwen3-30b-a3b-... Base model:qwen/qwen3-30b-a3b-... Base model:qwen/qwen3-coder-30... Codegen Conversational En Instruct Merge Qwen3 moe Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/YOYO-AI/Qwen3-30B-A3B-YOYO-V6

Qwen3 30B A3B YOYO V6 Parameters and Internals

LLM Name	Qwen3 30B A3B YOYO V6
Repository 🤗	https://huggingface.co/YOYO-AI/Qwen3-30B-A3B-YOYO-V6
Base Model(s)	Qwen3 30B A3B Instruct 2507 Qwen3 30B A3B Thinking 2507 Qwen3 Coder 30B A3B Instruct Qwen3 30B A3B Base Qwen/Qwen3-30B-A3B-Instruct-2507 Qwen/Qwen3-30B-A3B-Thinking-2507 Qwen/Qwen3-Coder-30B-A3B-Instruct Qwen/Qwen3-30B-A3B-Base
Model Size	30b
Required VRAM	61.1 GB
Updated	2026-08-06
Maintainer	YOYO-AI
Model Type	qwen3_moe
Instruction-Based	Yes
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
Supported Languages	en zh
Generates Code	Yes
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 YOYO V6 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 YOYO V6

Best Alternatives	Context / RAM	Downloads	Likes
...LL MASTER CODER M 1million Ctx	1024K / 84.8 GB	140	10
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
...en3 Coder 30B A3B Instruct FP8	256K / 31.2 GB	1556690	191
Tiny Pickle V3 Coder	256K / 61.2 GB	64	0
Qwen3 Coder 30B A3B Instruct	256K / 61.1 GB	9034	27
Qwen3 Coder REAP 25B A3B	256K / 49.8 GB	579	88

Note: green Score (e.g. "73.2") means that the model is better than YOYO-AI/Qwen3-30B-A3B-YOYO-V6.