What are the hardware requirements for Qwen3 235B A22B AWQ?

Qwen3 235B A22B AWQ requires approximately 124.1 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 235B A22B AWQ and how large is it?

Qwen3 235B A22B AWQ is developed by cognitivecomputations, a model with 235b 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 235B A22B AWQ?

Qwen3 235B A22B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 235B A22B AWQ by cognitivecomputations — VRAM 124.1GB, 40K context

Name: Qwen3 235B A22B AWQ
Author: cognitivecomputations

Qwen3 235B A22B AWQ is an open-source language model by cognitivecomputations. Features: 235b LLM, VRAM: 124.1GB, Context: 40K, License: apache-2.0, Quantized, LLM Explorer Score: 0.19.

Arxiv:2309.00071 4-bit Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen3-235b-a22... Conversational Endpoints compatible Quantized Qwen3 moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/QuixiAI/Qwen3-235B-A22B-AWQ

Qwen3 235B A22B AWQ Parameters and Internals

LLM Name	Qwen3 235B A22B AWQ
Repository 🤗	https://huggingface.co/QuixiAI/Qwen3-235B-A22B-AWQ
Base Model(s)	Qwen3 235B A22B Qwen/Qwen3-235B-A22B
Model Size	235b
Required VRAM	124.1 GB
Updated	2026-08-06
Maintainer	cognitivecomputations
Model Type	qwen3_moe
Model Files	5.0 GB: 1-of-25 5.0 GB: 2-of-25 5.0 GB: 3-of-25 5.0 GB: 4-of-25 5.0 GB: 5-of-25 5.0 GB: 6-of-25 5.0 GB: 7-of-25 5.0 GB: 8-of-25 5.0 GB: 9-of-25 5.0 GB: 10-of-25 5.0 GB: 11-of-25 5.0 GB: 12-of-25 5.0 GB: 13-of-25 5.0 GB: 14-of-25 5.0 GB: 15-of-25 5.0 GB: 16-of-25 5.0 GB: 17-of-25 5.0 GB: 18-of-25 5.0 GB: 19-of-25 5.0 GB: 20-of-25 5.0 GB: 21-of-25 5.0 GB: 22-of-25 5.0 GB: 23-of-25 5.0 GB: 24-of-25 4.1 GB: 25-of-25
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen3 235B A22B AWQ 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 235B A22B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...n3 235B A22B Instruct 2507 AWQ	256K / 124.1 GB	1697	4
Qwen3 235B A22B AWQ	40K / 124.1 GB	4322	11
...3 235B A22B Instruct 2507 4bit	256K / 131.4 GB	2658	3
...3 235B A22B Instruct 2507 8bit	256K / 227.7 GB	2591	2
...3 235B A22B Thinking 2507 8bit	256K / 227.7 GB	515	4
...5B A22B Thinking 2507 3bit DWQ	256K / 103 GB	204	6
...5B A22B Instruct 2507 3bit DWQ	256K / 103 GB	174	5
...5B A22B Thinking 2507 4bit DWQ	256K / 131.4 GB	65	4
...5B A22B Instruct 2507 4bit DWQ	256K / 131.4 GB	66	2
Qwen3 235B A22B 4bit	40K / 131.4 GB	2526	9

Note: green Score (e.g. "73.2") means that the model is better than QuixiAI/Qwen3-235B-A22B-AWQ.