What are the hardware requirements for Phi4 Mini Prose2Tags 4B?

Phi4 Mini Prose2Tags 4B requires approximately 7.7 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Phi4 Mini Prose2Tags 4B and how large is it?

Phi4 Mini Prose2Tags 4B is developed by USS-Inferprise, a model with 4b 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 Phi4 Mini Prose2Tags 4B?

Phi4 Mini Prose2Tags 4B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Phi4 Mini Prose2Tags 4B by USS-Inferprise — VRAM 7.7GB, 128K context

Name: Phi4 Mini Prose2Tags 4B
Author: USS-Inferprise

Phi4 Mini Prose2Tags 4B is an open-source language model by USS-Inferprise. Features: 4b LLM, VRAM: 7.7GB, Context: 128K, License: mit, Instruction-Based, LLM Explorer Score: 0.23.

Anime Base model:finetune:huihui-ai/... Base model:huihui-ai/phi-4-min... Conversational Custom code Danbooru Dataset:uss-inferprise/phi4-mi... En Endpoints compatible Finetuned Image-captioning Instruct Mergekit Phi-4 Phi3 Region:us Safetensors Tagging Unsloth

Model Card on HF 🤗: https://huggingface.co/USS-Inferprise/Phi4-Mini-Prose2Tags-4B

Phi4 Mini Prose2Tags 4B Parameters and Internals

LLM Name	Phi4 Mini Prose2Tags 4B
Repository 🤗	https://huggingface.co/USS-Inferprise/Phi4-Mini-Prose2Tags-4B
Base Model(s)	...hi 4 Mini Instruct Abliterated huihui-ai/Phi-4-mini-instruct-abliterated
Model Size	4b
Required VRAM	7.7 GB
Updated	2026-08-06
Maintainer	USS-Inferprise
Model Type	phi3
Instruction-Based	Yes
Model Files	7.7 GB
Supported Languages	en
Model Architecture	Phi3ForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	5.5.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	200064

Rank the Phi4 Mini Prose2Tags 4B 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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