What are the hardware requirements for Venti Blend Sce?

Venti Blend Sce requires approximately 43.2 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 Blend Sce and how large is it?

Venti Blend Sce 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 Blend Sce?

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

Venti Blend Sce by Quazim0t0 — VRAM 43.2GB, 16K context

Name: Venti Blend Sce
Author: Quazim0t0

Venti Blend Sce is an open-source language model by Quazim0t0. Features: 20b LLM, VRAM: 43.2GB, Context: 16K, Merged, LLM Explorer Score: 0.28.

Merged Model Base model:finetune:unsloth/ph... Base model:unsloth/phi-4 Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Quazim0t0/Venti-Blend-sce

Venti Blend Sce Parameters and Internals

LLM Name	Venti Blend Sce
Repository 🤗	https://huggingface.co/Quazim0t0/Venti-Blend-sce
Base Model(s)	Phi 4 unsloth/phi-4
Merged Model	Yes
Model Size	20b
Required VRAM	43.2 GB
Updated	2025-03-18
Maintainer	Quazim0t0
Model Type	llama
Model Files	5.0 GB: 1-of-9 5.0 GB: 2-of-9 5.0 GB: 3-of-9 4.9 GB: 4-of-9 5.0 GB: 5-of-9 5.0 GB: 6-of-9 5.0 GB: 7-of-9 4.9 GB: 8-of-9 3.4 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

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Instruction Following and Task Automation
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