What are the hardware requirements for Venti 20B?

Venti 20B requires approximately 43.1 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Venti 20B and how large is it?

Venti 20B is developed by Quazim0t0, a model with 20b 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 Venti 20B?

Venti 20B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Venti 20B by Quazim0t0 — VRAM 43.1GB, 16K context

Name: Venti 20B
Author: Quazim0t0

Venti 20B is an open-source language model by Quazim0t0. Features: 20b LLM, VRAM: 43.1GB, Context: 16K, Merged, LLM Explorer Score: 0.27.

Merged Model Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Quazim0t0/Venti-20b

Venti 20B Parameters and Internals

LLM Name	Venti 20B
Repository 🤗	https://huggingface.co/Quazim0t0/Venti-20b
Merged Model	Yes
Model Size	20b
Required VRAM	43.1 GB
Updated	2025-03-18
Maintainer	Quazim0t0
Model Type	llama
Model Files	5.0 GB: 1-of-9 4.8 GB: 2-of-9 4.9 GB: 3-of-9 5.0 GB: 4-of-9 4.9 GB: 5-of-9 5.0 GB: 6-of-9 5.0 GB: 7-of-9 5.0 GB: 8-of-9 3.5 GB: 9-of-9
Model Architecture	LlamaForCausalLM
Context Length	16384
Model Max Length	16384
Transformers Version	4.47.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|dummy_87\|>
Vocabulary Size	100352
Torch Data Type	bfloat16

Rank the Venti 20B capabilities

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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

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