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

Qwen3 30B A3B Instruct 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 Instruct 2507 and how large is it?

Qwen3 30B A3B Instruct 2507 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.

How does Qwen3 30B A3B Instruct 2507 perform on standard benchmarks?

Qwen3 30B A3B Instruct 2507 has the following published scores: LMSYS ELO 1382. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen3 30B A3B Instruct 2507 by unsloth — VRAM 61.1GB, 256K context

Name: Qwen3 30B A3B Instruct 2507
Author: unsloth

Qwen3 30B A3B Instruct 2507 is an open-source language model by unsloth. Features: 30b LLM, VRAM: 61.1GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.36, ELO: 1382.

Arxiv:2505.09388 Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-30b-a3b-... Conversational Endpoints compatible Instruct Qwen3 moe Region:us Safetensors Sharded Tensorflow Unsloth

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

Qwen3 30B A3B Instruct 2507 Benchmarks

LMSys ELO 1382 vs 1272 (so35) 8.6%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen3 30B A3B Instruct 2507 Parameters and Internals

LLM Name	Qwen3 30B A3B Instruct 2507
Repository 🤗	https://huggingface.co/unsloth/Qwen3-30B-A3B-Instruct-2507
Base Model(s)	Qwen3 30B A3B Instruct 2507 Qwen/Qwen3-30B-A3B-Instruct-2507
Model Size	30b
Required VRAM	61.1 GB
Updated	2026-08-05
Maintainer	unsloth
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
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.54.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 30B A3B 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

Best Alternatives to Qwen3 30B A3B Instruct 2507

Best Alternatives	Context / RAM	Downloads	Likes
...LL MASTER CODER M 1million Ctx	1024K / 84.8 GB	194	11
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	1903736	824
...en3 Coder 30B A3B Instruct FP8	256K / 31.2 GB	1556690	191
Lynx Instruct 30B	256K / 61.1 GB	223244	4
...wen3 30B A3B Instruct 2507 FP8	256K / 31.2 GB	565533	130

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