Skip to content
← Models
ClosedMicrosoft/10 trustMetrics-checked

Florence

Vision foundation model unifying tasks across the space-time-modality spectrum.

Visit official page →

About

Florence is Microsoft's computer vision foundation model, published in November 2021. It expands visual representations from coarse (scene) to fine (object), from static images to dynamic video, and from RGB to multiple modalities such as captions and depth, trained on web-scale image-text data.

The model achieved state-of-the-art results across 44 representative benchmarks, including 83.74% top-1 zero-shot accuracy on ImageNet-1K and strong transfer on COCO detection, VQA, and Kinetics action recognition. It adapts with minimal customization through fine-tuning, linear probing, or few-shot transfer.

Florence later shipped as the vision backbone of Azure AI Vision services, powering production captioning, retrieval, and video summarization. The foundation weights themselves were not open-sourced.

Specs

Context window

Pricing

Free quota

API access

Weights

Closed — API only

Released

November 22, 2021

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

image-classificationobject-detectionvisual-question-answeringvideo-retrieval

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 86; Trending score 68/100 from researcher assessment.

More in the florence family

Sources