What are the hardware requirements for Phi 4 Mm Binary QA NI 0415 1764?

Phi 4 Mm Binary QA NI 0415 1764 requires approximately 11.2 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 Mm Binary QA NI 0415 1764 and how large is it?

Phi 4 Mm Binary QA NI 0415 1764 is developed by ntnu-smil, a model with 5.6b 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 Mm Binary QA NI 0415 1764?

Phi 4 Mm Binary QA NI 0415 1764 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Phi 4 Mm Binary QA NI 0415 1764 by ntnu-smil — VRAM 11.2GB, 128K context

Name: Phi 4 Mm Binary QA NI 0415 1764
Author: ntnu-smil

Phi 4 Mm Binary QA NI 0415 1764 is an open-source language model by ntnu-smil. Features: 5.6b LLM, VRAM: 11.2GB, Context: 128K, License: mit, Instruction-Based, LLM Explorer Score: 0.17.

Base model:finetune:microsoft/... Base model:microsoft/phi-4-mul... Conversational Custom code Generated from trainer Instruct Phi4mm Region:us Safetensors Sharded Tensorboard Tensorflow

Model Card on HF 🤗: https://huggingface.co/ntnu-smil/Phi-4-mm_Binary_QA_NI_0415_1764

Phi 4 Mm Binary QA NI 0415 1764 Parameters and Internals

LLM Name	Phi 4 Mm Binary QA NI 0415 1764
Repository 🤗	https://huggingface.co/ntnu-smil/Phi-4-mm_Binary_QA_NI_0415_1764
Base Model(s)	Phi 4 Multimodal Instruct microsoft/Phi-4-multimodal-instruct
Model Size	5.6b
Required VRAM	11.2 GB
Updated	2026-08-07
Maintainer	ntnu-smil
Model Type	phi4mm
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-3 5.0 GB: 2-of-3 1.2 GB: 3-of-3 0.0 GB
Model Architecture	Phi4MMForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.48.2
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	200064
Torch Data Type	bfloat16

Rank the Phi 4 Mm Binary QA NI 0415 1764 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

Best Alternatives to Phi 4 Mm Binary QA NI 0415 1764

Best Alternatives	Context / RAM	Downloads	Likes
Phi 4 Multimodal Instruct	128K / 11.2 GB	548715	1609
...Mm Lttc Binary Integrated 1764	128K / 33.6 GB	6	0
... Instruct QA NoImage 0325 1964	128K / 11.2 GB	73	0
... Multimodal Instruct 0401V1 V1	128K / 11.2 GB	8	0
... Multimodal Instruct 0401V1 V1	128K / 11.2 GB	7	0
... Multimodal Instruct 0401V1 V1	128K / 11.2 GB	6	0
...modal Instruct QA NoImage 0325	128K / 11.2 GB	10	0
...dal Instruct Lttc NoQA NoImage	128K / 11.2 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than ntnu-smil/Phi-4-mm_Binary_QA_NI_0415_1764.