What are the hardware requirements for WizardLM 2 8x22B AWQ?

WizardLM 2 8x22B AWQ requires approximately 73.7 GB of VRAM and supports a context window of 64K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed WizardLM 2 8x22B AWQ and how large is it?

WizardLM 2 8x22B AWQ is developed by MaziyarPanahi, a model with 140.6b 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 WizardLM 2 8x22B AWQ?

WizardLM 2 8x22B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

WizardLM 2 8x22B AWQ by MaziyarPanahi — VRAM 73.7GB, 64K context

Name: WizardLM 2 8x22B AWQ
Author: MaziyarPanahi

WizardLM 2 8x22B AWQ is an open-source language model by MaziyarPanahi. Features: 140.6b LLM, VRAM: 73.7GB, Context: 64K, MoE, Quantized, LLM Explorer Score: 0.12.

4-bit Awq Base model:microsoft/wizardlm-... Base model:quantized:microsoft... Conversational Finetuned Mixtral Moe Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/WizardLM-2-8x22B-AWQ

WizardLM 2 8x22B AWQ Parameters and Internals

Model Type

text-generation

Additional Notes

The model is a quantized (AWQ) version, optimized for improved performance in text generation.

LLM Name	WizardLM 2 8x22B AWQ
Repository 🤗	https://huggingface.co/MaziyarPanahi/WizardLM-2-8x22B-AWQ
Model Name	WizardLM-2-8x22B-AWQ
Base Model(s)	microsoft/WizardLM-2-8x22B microsoft/WizardLM-2-8x22B
Model Size	140.6b
Required VRAM	73.7 GB
Updated	2026-07-13
Maintainer	MaziyarPanahi
Model Type	mixtral
Model Files	5.0 GB: 1-of-15 5.0 GB: 2-of-15 5.0 GB: 3-of-15 5.0 GB: 4-of-15 5.0 GB: 5-of-15 5.0 GB: 6-of-15 5.0 GB: 7-of-15 5.0 GB: 8-of-15 5.0 GB: 9-of-15 5.0 GB: 10-of-15 5.0 GB: 11-of-15 5.0 GB: 12-of-15 5.0 GB: 13-of-15 5.0 GB: 14-of-15 3.7 GB: 15-of-15
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MixtralForCausalLM
Context Length	65536
Model Max Length	65536
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the WizardLM 2 8x22B 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 WizardLM 2 8x22B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...ixtral 8x22B Instruct V0.1 AWQ	64K / 73.7 GB	6689	13
...olphin 2.9.2 Mixtral 8x22b AWQ	64K / 73.7 GB	51	0
Mixtral 8x22B V0.1 AWQ	64K / 73.7 GB	358	36
Karasu Mixtral 8x22B V0.1 AWQ	64K / 73.7 GB	5	7
Zephyr Orpo 141B A35b V0.1 AWQ	64K / 73.7 GB	4	3
Mixtral 8x22B Instruct V0.1	64K / 221.4 GB	71589	756
Zephyr Orpo 141B A35b V0.1	64K / 207.2 GB	66	270
WizardLM 2 8x22B	64K / 216.8 GB	9656	415
Mixtral 8x22B V0.1	64K / 221.6 GB	5069	239
...ixtral 8x22B Instruct V0.1 FP8	64K / 140.9 GB	11259	0

Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/WizardLM-2-8x22B-AWQ.