LLM Reference

Florence 2 Base

Released
2024-06-10
Last refreshed
2026-04-15
Status
Researched 154d ago

Florence 2 Base has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Use it for

  • Teams evaluating general LLM work

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Released
2024-06-10
Parameters
230M
Architecture
Decoder Only
Specialization
general
Training
finetuned
Created by

Advancing the state-of-the-art in AI and computing.

Redmond, Washington, United States
Founded 1991
Website
Pricing

No tracked provider token pricing is available yet.

About

Florence-2 Base is a compact, open-source vision-language model by Microsoft designed to tackle a diverse range of vision tasks through a unified sequence-to-sequence framework 1210. It seamlessly processes images and text prompts for tasks such as captioning, object detection, segmentation, and visual grounding, all managed through a single set of parameters guided by task-specific prompts 34. With a relatively small size of 0.23 billion parameters, it is optimized for devices with limited computational resources, yet its performance is comparable to larger models, owing to its training on the expansive FLD-5B dataset with 5.4 billion annotations across 126 million images 47.

Florence 2 Base is a model in the Florence 2 family. No headline benchmark score is tracked for Florence 2 Base yet.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.

Rankings & picks(4)