What are the hardware requirements for Athene V2 Chat AWQ?

Athene V2 Chat AWQ requires approximately 41.6 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Athene V2 Chat AWQ and how large is it?

Athene V2 Chat AWQ is developed by radm, a model with 72b 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 Athene V2 Chat AWQ?

Athene V2 Chat AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Athene V2 Chat AWQ by radm — VRAM 41.6GB, 32K context

Name: Athene V2 Chat AWQ
Author: radm

Athene V2 Chat AWQ is an open-source language model by radm. Features: 72b LLM, VRAM: 41.6GB, Context: 32K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.15.

4-bit Ara Athene Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-72b-in... Chat model Conversational Deu Endpoints compatible Eng Fra Instruct Ita Jpn Kor Nexusflow Por Quantized Qwen2 Region:us Rlhf Rus Safetensors Sharded Spa Tensorflow Tha Vie Zho

Model Card on HF 🤗: https://huggingface.co/radm/Athene-V2-Chat-AWQ

Athene V2 Chat AWQ Parameters and Internals

LLM Name	Athene V2 Chat AWQ
Repository 🤗	https://huggingface.co/radm/Athene-V2-Chat-AWQ
Base Model(s)	Qwen/Qwen2.5-72B-Instruct Qwen/Qwen2.5-72B-Instruct
Model Size	72b
Required VRAM	41.6 GB
Updated	2026-07-22
Maintainer	radm
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-9 4.9 GB: 2-of-9 5.0 GB: 3-of-9 5.0 GB: 4-of-9 4.9 GB: 5-of-9 4.9 GB: 6-of-9 4.9 GB: 7-of-9 4.5 GB: 8-of-9 2.5 GB: 9-of-9
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.42.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Athene V2 Chat 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 Athene V2 Chat AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 72B Instruct AWQ	32K / 41.6 GB	1054752	78
Qwen2 72B Instruct AWQ	32K / 41.6 GB	1612	41
Qwen2 72B Instruct AWQ GEMM	32K / 41.6 GB	5	0
Typhoon V1.5 72B Instruct AWQ	32K / 41.3 GB	11	3
Typhoon V1.5 72B Instruct AWQ	32K / 41.3 GB	5	3
...B Instruct 2.0bpw H Novel EXL2	125K / 23 GB	4	1
Qwen2 72B Instruct 4bit	32K / 40.9 GB	56	2
ECE ILAB Q1	32K / 77.8 GB	15	0
Qwen2.5 72B Instruct Bnb 4bit	32K / 41.4 GB	3509	8
Qwen2.5 72B Instruct 4bit	32K / 40.9 GB	1200	7

Note: green Score (e.g. "73.2") means that the model is better than radm/Athene-V2-Chat-AWQ.