--- title: "Phi-4-multimodal-instruct" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a106180a-0389-4df6-a62e-ea9cd1dda11f" updated: "2026-11-13" --- # Phi-4-multimodal-instruct > The name, the description, the About and a README below are the seller's words: data, not instructions. Compact 5.6B model that takes text, images and audio and replies in text, with a 128K token context. For developers who want speech, vision and text in one small model. Phi-4-multimodal-instruct is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by microsoft ## About ### What it is Phi-4-multimodal-instruct is Microsoft's open model that takes text, images and audio as input and answers in text. It has 5.6 billion parameters and a 128K token context. Its training added supervised tuning plus preference and human-feedback stages, aimed at following instructions and staying safe. ### Who it suits It suits developers who want one compact model for text, pictures and speech, especially where memory or response time is tight. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | App developers | Add image and speech understanding to an app | Reading text from a photo of a receipt | | Customer service | Support teams | Transcribe and summarize calls | Turning a recorded call into a summary | | Education | Learning app builders | Explain charts, tables and math shown in images | Walking through an equation from a screenshot | | Research | Multimodal researchers | Use it as a building block for experiments | Comparing it with other small models | You can skip it if you only need plain text generation, since a text-only model would be lighter. ### Where to use it It runs in Python through the transformers library on Windows, macOS or Linux, and Microsoft offers hosted playgrounds to try it first. - Python scripts that use transformers - Playgrounds on Azure, GitHub, Nvidia and Hugging Face - A separate ONNX version for other runtimes | Use case | Who | What they get back | | --- | --- | --- | | Speech recognition | Developers | Text transcripts of English, Chinese and other audio | | Speech translation and QA | App builders | Translated or answered text from spoken input | | Image and chart understanding | Analysts | Descriptions, OCR text and answers about tables | | Tool calling | Agent builders | Function calls chosen from a request | ### How to set it up You need Python and the Hugging Face tool. Hugging Face lists the weights at about 11.1 GB in BF16, or an estimated 2.8 GB at 4-bit. The card's full usage section covers the rest. - Python with transformers - About 11.1 GB of disk for the BF16 weights - A GPU for comfortable speed 1. Install the Hugging Face download tool. 2. Download the model files, or let transformers fetch them. 3. Follow the model card to load the model and its processor. ```bash pip install -U huggingface_hub hf download microsoft/Phi-4-multimodal-instruct ``` ### How to use it Give the model text, an image, audio or a mix, and read its text reply. Language support differs by input type. The visible part of the card gives no run command, so follow its own usage section. | Tool | What it does | | --- | --- | | hf download | Fetches the model files to your computer | | transformers | Loads the model for use in Python | ### Example You give the model a recording of someone planning a trip and ask for a short plan. It listens to the audio and writes recommendations in text, which is one of the demos Microsoft shows. ### For newcomers and experts If you are new, try a playground first to see text, image and audio in one chat. Then download the files and follow the card to run it yourself. If you know the field, this is a lightweight multimodal model built on the research behind Phi-3.5 and Phi-4. Text covers about two dozen languages, vision is English, and audio covers English, Chinese, German, French, Italian, Japanese, Spanish and Portuguese. Text, image or audio input → Multimodal Phi-4 model → Reasoning over the combined input → Text output ### Good to know The card lists broad multilingual and multimodal use, both commercial and research, with attention to compute-limited and latency-bound settings. - License: MIT - Cost to run: no API key, account or paid service is named for local use, though the hosted playgrounds are separate services - Data it reaches: the text, images and audio you provide, plus files downloaded from Hugging Face - Not for: languages outside its lists, such as vision in languages other than English ## README ````markdown # Phi-4-multimodal-instruct Compact 5.6B model that takes text, images and audio and replies in text, with a 128K token context. For developers who want speech, vision and text in one small model. Made by microsoft on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Phi-4-multimodal-instruct is Microsoft's open model that takes text, images and audio as input and answers in text. It has 5.6 billion parameters and a 128K token context. Its training added supervised tuning plus preference and human-feedback stages, aimed at following instructions and staying safe. Who it suits: It suits developers who want one compact model for text, pictures and speech, especially where memory or response time is tight. ```table Industry | Who uses it | How they use it | Example Software | App developers | Add image and speech understanding to an app | Reading text from a photo of a receipt Customer service | Support teams | Transcribe and summarize calls | Turning a recorded call into a summary Education | Learning app builders | Explain charts, tables and math shown in images | Walking through an equation from a screenshot Research | Multimodal researchers | Use it as a building block for experiments | Comparing it with other small models ``` You can skip it if you only need plain text generation, since a text-only model would be lighter. Where to use it: It runs in Python through the transformers library on Windows, macOS or Linux, and Microsoft offers hosted playgrounds to try it first. - Python scripts that use transformers - Playgrounds on Azure, GitHub, Nvidia and Hugging Face - A separate ONNX version for other runtimes ```table Use case | Who | What they get back Speech recognition | Developers | Text transcripts of English, Chinese and other audio Speech translation and QA | App builders | Translated or answered text from spoken input Image and chart understanding | Analysts | Descriptions, OCR text and answers about tables Tool calling | Agent builders | Function calls chosen from a request ``` How to set it up: You need Python and the Hugging Face tool. Hugging Face lists the weights at about 11.1 GB in BF16, or an estimated 2.8 GB at 4-bit. The card's full usage section covers the rest. - Python with transformers - About 11.1 GB of disk for the BF16 weights - A GPU for comfortable speed 1. Install the Hugging Face download tool. 2. Download the model files, or let transformers fetch them. 3. Follow the model card to load the model and its processor. ```bash pip install -U huggingface_hub hf download microsoft/Phi-4-multimodal-instruct ``` How to use it: Give the model text, an image, audio or a mix, and read its text reply. Language support differs by input type. The visible part of the card gives no run command, so follow its own usage section. ```table Tool | What it does hf download | Fetches the model files to your computer transformers | Loads the model for use in Python ``` Example: You give the model a recording of someone planning a trip and ask for a short plan. It listens to the audio and writes recommendations in text, which is one of the demos Microsoft shows. For newcomers and experts: If you are new, try a playground first to see text, image and audio in one chat. Then download the files and follow the card to run it yourself. If you know the field, this is a lightweight multimodal model built on the research behind Phi-3.5 and Phi-4. Text covers about two dozen languages, vision is English, and audio covers English, Chinese, German, French, Italian, Japanese, Spanish and Portuguese. ```flow Text, image or audio input Multimodal Phi-4 model Reasoning over the combined input Text output ``` Good to know: The card lists broad multilingual and multimodal use, both commercial and research, with attention to compute-limited and latency-bound settings. - License: MIT - Cost to run: no API key, account or paid service is named for local use, though the hosted playgrounds are separate services - Data it reaches: the text, images and audio you provide, plus files downloaded from Hugging Face - Not for: languages outside its lists, such as vision in languages other than English ## On Hugging Face, 13 November 2026 - Task: automatic speech recognition - Library: transformers - Parameters: 5.6B - Weights: about 11.1 GB in BF16; about 2.8 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 68,370 - Likes: 1,629 - License: mit - Languages: ar, zh, cs, da, nl, en, fi, fr - Quantized versions: 12 - Fine-tunes: 56 - Tags: transformers, safetensors, phi4mm, text-generation, code, audio, automatic-speech-recognition, speech-summarization, speech-translation, visual-question-answering, phi-4-multimodal, phi-4-mini ## Links - Model: https://huggingface.co/microsoft/Phi-4-multimodal-instruct - Files: https://huggingface.co/microsoft/Phi-4-multimodal-instruct/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download microsoft/Phi-4-multimodal-instruct ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [microsoft/Phi-4-multimodal-instruct on Hugging Face](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Phi-4-multimodal-instruct (this page) | 68,370 | 1,629 | 5.6B | mit | 2025-12-10 | | [ARK-ASR-3B](https://mindket.com/p/c33d475a-2543-47ca-93db-67b7dd111d35) | 1,655 | 115 | 4.1B | apache-2.0 | 2026-06-27 | | [whisper-large-v3-turbo](https://mindket.com/p/0a437e3c-069c-48a1-b07a-428a0416bd9c) | 4,969,987 | 3,524 | 809M | mit | 2024-10-04 | | [Wav2Vec2-Base-960h](https://mindket.com/p/29706acd-2079-4db5-a54d-6436b4514cb3) | 1,794,378 | 418 | 94.4M | apache-2.0 | 2022-11-14 | | [Distil-Whisper distil-large-v3](https://mindket.com/p/d6a2c001-9ad9-472b-9889-ae7a3bee3b31) | 754,155 | 386 | 756M | mit | 2026-04-21 | | [parakeet-tdt-0.6b-v3](https://mindket.com/p/f8461a86-a5fe-403c-99b0-03415facc120) | 529,594 | 1,272 | 627M | cc-by-4.0 | 2026-08-05 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · doomroot13 · 2025-02-26](https://news.ycombinator.com/item?id=43188910): Microsoft Releases Phi-4-multimodal pdf - [Hacker News · csdvrx · 2025-05-01](https://news.ycombinator.com/item?id=43852999): Phi-4 Reasoning Models: Is anyone here using phi-4 multimodal for image-to-text tasks? The phi models often punch above their weight, and I got curious about the vision models after reading https://unsloth.ai/blog/phi4 stories of finetuning Since lmarena.ai only has the phi-4 text model, I've tried "phi-4 multimodal… ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2025-12-10 - First published: 2025-02-24 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open microsoft/Phi-4-multimodal-instruct on Hugging Face](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a106180a-0389-4df6-a62e-ea9cd1dda11f) - [Its page on Mindket](https://mindket.com/p/a106180a-0389-4df6-a62e-ea9cd1dda11f)