What are the hardware requirements for Qwen3 235B A22B Instruct 2507 AWQ?

Qwen3 235B A22B Instruct 2507 AWQ requires approximately 124.1 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 235B A22B Instruct 2507 AWQ and how large is it?

Qwen3 235B A22B Instruct 2507 AWQ is developed by koushd, 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 Instruct 2507 AWQ?

Qwen3 235B A22B Instruct 2507 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 Instruct 2507 AWQ by koushd — VRAM 124.1GB, 256K context

Name: Qwen3 235B A22B Instruct 2507 AWQ
Author: koushd

Qwen3 235B A22B Instruct 2507 AWQ is an open-source language model by koushd. Features: 235b LLM, VRAM: 124.1GB, Context: 256K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.21.

Arxiv:2505.09388 4-bit Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen3-235b-a22... Conversational Endpoints compatible Instruct Quantized Qwen3 Qwen3 moe Region:us Safetensors Sharded Tensorflow Vllm 量化修复

Model Card on HF 🤗: https://huggingface.co/koushd/Qwen3-235B-A22B-Instruct-2507-AWQ

Qwen3 235B A22B Instruct 2507 AWQ Parameters and Internals

LLM Name	Qwen3 235B A22B Instruct 2507 AWQ
Repository 🤗	https://huggingface.co/koushd/Qwen3-235B-A22B-Instruct-2507-AWQ
Base Model(s)	Qwen3 235B A22B Instruct 2507 Qwen/Qwen3-235B-A22B-Instruct-2507
Model Size	235b
Required VRAM	124.1 GB
Updated	2026-04-11
Maintainer	koushd
Model Type	qwen3_moe
Instruction-Based	Yes
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	262144
Model Max Length	262144
Transformers Version	4.51.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen3 235B A22B Instruct 2507 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 Instruct 2507 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...3 235B A22B Instruct 2507 4bit	256K / 131.4 GB	2658	3
...3 235B A22B Instruct 2507 8bit	256K / 227.7 GB	2591	2
...5B A22B Instruct 2507 3bit DWQ	256K / 103 GB	174	5
...5B A22B Instruct 2507 4bit DWQ	256K / 131.4 GB	66	2
...en3 235B A22B Instruct 2507 1M	986K / 171.9 GB	4	1
Qwen3 235B A22B Instruct 2507	256K / 167.9 GB	28	10
Qwen3 235B A22B Instruct 2507	256K / 171.9 GB	59472	793
Vivo C V1	256K / 156.4 GB	415	2
... 235B A22B Instruct 2507 NVFP4	256K / 139.2 GB	14322	10
...n3 235B A22B Instruct 2507 FP8	256K / 236.5 GB	54126	147

Note: green Score (e.g. "73.2") means that the model is better than koushd/Qwen3-235B-A22B-Instruct-2507-AWQ.