What are the hardware requirements for Phi 4 Mini Instruct 8bit?

Phi 4 Mini Instruct 8bit requires approximately 4.1 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 Phi 4 Mini Instruct 8bit and how large is it?

Phi 4 Mini Instruct 8bit is developed by mlx-community, a model with 1.1b 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 Phi 4 Mini Instruct 8bit?

Phi 4 Mini Instruct 8bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Phi 4 Mini Instruct 8bit by mlx-community — VRAM 4.1GB, 128K context

Name: Phi 4 Mini Instruct 8bit
Author: mlx-community

Phi 4 Mini Instruct 8bit is an open-source language model by mlx-community. Features: 1.1b LLM, VRAM: 4.1GB, Context: 128K, License: mit, Quantized, Instruction-Based, LLM Explorer Score: 0.18.

8-bit 8bit Base model:microsoft/phi-4-min... Base model:quantized:microsoft... Code Conversational Custom code Endpoints compatible Instruct Mlx Mlx-my-repo Multilingual Phi3 Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mlx-community/Phi-4-mini-instruct-8bit

Phi 4 Mini Instruct 8bit Parameters and Internals

LLM Name	Phi 4 Mini Instruct 8bit
Repository 🤗	https://huggingface.co/mlx-community/Phi-4-mini-instruct-8bit
Base Model(s)	Phi 4 Mini Instruct microsoft/Phi-4-mini-instruct
Model Size	1.1b
Required VRAM	4.1 GB
Updated	2026-07-26
Maintainer	mlx-community
Model Type	phi3
Instruction-Based	Yes
Model Files	4.1 GB
Quantization Type	8bit
Model Architecture	Phi3ForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.0
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	200064
Torch Data Type	bfloat16

Rank the Phi 4 Mini Instruct 8bit 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 Phi 4 Mini Instruct 8bit

Best Alternatives	Context / RAM	Downloads	Likes
Phi 3 Mini 128K Instruct 8bit	128K / 4.1 GB	49	10
Phi 3.5 Mini Instruct 8bit	128K / 4.1 GB	56	6
Phi3 Gptq 8bits	4K / 4.1 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Phi-4-mini-instruct-8bit.