Claude Opus 4.6 vs Florence-2

Compare Claude Opus 4.6 and Florence-2 side-by-side. See how these vision models stack up in OCR, Object Detection, and Image Captioning.

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AnthropicClaude Opus 4.6
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AzureFlorence-2
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Claude Opus 4.6 vs Florence-2: Overview

Claude Opus 4.6

Claude Opus 4.6 is the flagship large language model from Anthropic, released on 2026-02-05 for advanced reasoning, complex coding, and enterprise agent workflows. It supports text and image inputs via API, offers a 200K-token standard context window with a 1M-token beta option, and enables outputs up to 128K tokens, with adaptive reasoning and context compaction for sustained tasks.

As of 2026-02-17, Anthropic also released Claude Sonnet 4.6, extending the 1M-token context window to a broader tier. Opus remains positioned for maximum depth and benchmark performance, while Sonnet 4.6 brings long-context capability to more cost- and latency-sensitive production use cases.

Florence-2

Florence-2, introduced by Microsoft Research at CVPR 2024, is an open-source vision-language foundation model designed to unify diverse computer vision tasks within a single sequence-to-sequence framework. Unlike traditional models that specialize in specific tasks, Florence-2 accepts both images and text prompts and outputs text for tasks such as captioning, object detection, segmentation, OCR, and region-based grounding. It comes in two sizes—Florence-2-base (~230M parameters) and Florence-2-large (~770M parameters)—and is trained on FLD-5B, a large dataset of ~126M images with ~5.4B annotations.

The model demonstrates strong zero-shot and fine-tuned performance, often rivaling larger vision-language systems while remaining lightweight and efficient. Released under the MIT license, all weights are publicly available, making it accessible for fine-tuning and deployment in applications like VQA, content tagging, accessibility, and research. Florence-2’s compact design, versatility, and openness position it as a practical alternative to larger proprietary multimodal models.

Claude Opus 4.6 vs Florence-2 Comparison Table

PropertyClaude Opus 4.6 Florence-2
OrganizationAnthropicMicrosoft
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Jun 2025
Context Window1.0M
Parameters230M
LicenseProprietaryMIT
Pricing per 1M tokens
Input $/1M$5.00
Output $/1M$25.00
Vision Tasks
CaptioningDemoDemo
Object DetectionDemoDemo
OCRDemoDemo
ClassificationDemo
Instance Segmentation
Open Vocabulary Object Detection
Phrase Grounding
Region Proposal
Vision Language
Visual Question AnsweringDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Zero-shot Detection
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
64.18%
Avg Response Time23.35s
Median input tokensincl. image tokens2.2K
Median output tokens130
Est. cost / taskon this benchmark$0.014
Defect Detection
73.3%(11/15)
Document Understanding
77.8%(7/9)
Object Counting
20%(2/10)
Object Understanding
71.4%(10/14)
Spatial Understanding
68.4%(13/19)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology