What are the hardware requirements for Genz 70B AWQ?

Genz 70B AWQ requires approximately 36.6 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Genz 70B AWQ and how large is it?

Genz 70B AWQ is developed by TheBloke, a model with 70b 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 Genz 70B AWQ?

Genz 70B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Genz 70B AWQ by TheBloke — VRAM 36.6GB, 4K context

Name: Genz 70B AWQ
Author: TheBloke

Genz 70B AWQ is an open-source language model by TheBloke. Features: 70b LLM, VRAM: 36.6GB, Context: 4K, License: llama2, Quantized, LLM Explorer Score: 0.09.

4-bit Awq Base model:budecosystem/genz-7... Base model:quantized:budecosys... En Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/Genz-70b-AWQ

Genz 70B AWQ Parameters and Internals

Model Type

llama

Use Cases

Applications:

Text summarization, Text generation, Chatbot creation

Considerations:

Out-of-Scope Usage: requires adequate risk assessment and mitigation.

Additional Notes

The model has been made more accessible with smaller quantization versions to facilitate use on personal computers.

Training Details

Data Sources:

OpenAssistant, Thought Source

Methodology:

Fine-tuning for Supervised Fine-Tuning (SFT)

Model Architecture:

auto-regressive language model with optimized transformer architecture

Input Output

Input Format:

Expected prompt: ### User: {prompt} ### Assistant: '

Accepted Modalities:

text

Release Notes

Version:

GenZ-70B

Date:

21 August 2023

Notes:

Released together with performance enhancements and quantized versions.

Version:

GenZ-13B V2

Date:

27 July 2023

Notes:

Improved evaluation results and various quantization options.

LLM Name	Genz 70B AWQ
Repository 🤗	https://huggingface.co/TheBloke/Genz-70b-AWQ
Model Name	GenZ 70B
Model Creator	Bud
Base Model(s)	Genz 70B budecosystem/genz-70b
Model Size	70b
Required VRAM	36.6 GB
Updated	2026-07-24
Maintainer	TheBloke
Model Type	llama
Model Files	9.9 GB: 1-of-4 9.9 GB: 2-of-4 9.9 GB: 3-of-4 6.9 GB: 4-of-4
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Genz 70B 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 Genz 70B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...0B Instruct Gradient 1048K AWQ	1024K / 39.9 GB	5	1
...70B Instruct Gradient 262K AWQ	256K / 39.9 GB	5	0
Llama 3.3 70B Instruct AWQ	128K / 39.9 GB	262002	46
...lama 3.3 70B Instruct AWQ INT4	128K / 39.9 GB	82744	30
Llama 3.3 70B Instruct AWQ	128K / 39.9 GB	16090	12
... SauerkrautLM 70B Instruct AWQ	128K / 39.9 GB	5	5
MultiVerse 70B AWQ	32K / 41.3 GB	70	2
Opus V1.2 70B AWQ	32K / 36.7 GB	9	1
QuartetAnemoi 70B T0.0001 AWQ	31K / 36.7 GB	3	1
Senku 70B AWQ 4bit GEMM	31K / 36.7 GB	2	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Genz-70b-AWQ.