Roboflow

Claude Sonnet 5.5 vs SAM 3

Compare Claude Sonnet 5.5 and SAM 3 side-by-side. See how these vision models stack up in Object Detection.

Compare Claude Sonnet 5.5 vs SAM 3 live

Run the same image across every model that supports a task and compare their outputs side-by-side.

Detect and compare bounding boxes across models on the same image.

Open Object Detection in the full playground
AnthropicClaude Sonnet 5.5
Run to compare this model.
MetaSAM 3
Run to compare this model.

Models in this comparison

Meta

Claude Sonnet 5.5 vs SAM 3 Comparison Table

Evals updated October 8, 2026Pricing updated October 10, 2026

PropertyClaude Sonnet 5.5SAM 3
OrganizationAnthropicMeta
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateSep 2026Nov 2025
Context Window1.0M—
ParametersUnknownUnknown
LicenseProprietaryCustom
Pricing per 1M tokens
Input $/1M$2.00No published price
Output $/1M$10.00No published price
Vision Tasks
Object DetectionDemoDemo
CaptioningDemoNot listed
Chart Question AnsweringSupportedNot listed
ClassificationDemoNot listed
Document Question AnsweringSupportedNot listed
Image TaggingSupportedNot listed
Instance SegmentationNot listedSupported
Multi-Label ClassificationSupportedNot listed
OCRDemoNot listed
Open Vocabulary Object DetectionNot listedSupported
Promptable Concept SegmentationNot listedDemo
Video Object TrackingNot listedSupported
Vision LanguageSupportedNot listed
Visual Question AnsweringDemoNot listed
Zero Shot SegmentationNot listedSupported
Model Features
Foundation VisionSupportedSupported
Multimodal VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedNot listed
Zero-shot DetectionNot listedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
77.6%
Not evaluated
Avg cost / sample$0.0073–
Avg speed / sample8.33s–
By task
Object Detection (low)
74.3%
±0.9, Mean of 3 runs, range 73.5 to 75.3
$0.0098
–
Object Detection (high)
76.8%
±0.4, Mean of 3 runs, range 76.5 to 77.3
$0.014
–
Counting (low)
79.3%
±0.7, Mean of 3 runs, range 78.4 to 79.7
$0.0042
–
Counting (high)
82.9%
±1.4, Mean of 3 runs, range 81.1 to 83.8
$0.0053
–
Identification (low)
91.7%
±3.1, Mean of 3 runs, range 87.5 to 93.8
$0.0029
–
Identification (high)
90.6%
±0.0, Mean of 3 runs, range 90.6 to 90.6
$0.0033
–
OCR
66.3%
$0.0075
–
by category
Single value
48.7%
Transcription
76.3%
Structured JSON
83.8%
Text localization
60.6%
Reasoning (low)
76.4%
±0.7, Mean of 3 runs, range 75.5 to 76.8
$0.0049
–
Reasoning (high)
83.9%
±1.7, Mean of 3 runs, range 82.1 to 85.4
$0.0061
–

Claude Sonnet 5.5 vs SAM 3: Overview

Claude Sonnet 5.5

Claude Sonnet 5.5 is a proprietary multimodal language model from Anthropic and the second release in the Claude 5.5 family, following Claude Opus 5.5. It accepts interleaved text and image input and returns text, operating with a 1M token context window and a maximum output of 128K tokens per request. The model uses adaptive thinking by default, allocating variable reasoning effort per request rather than exposing a manual extended thinking toggle, and its training data cutoff is June 2026. Anthropic positions it as a faster, lower cost complement to Opus 5.5 for well scoped everyday tasks, bug fixing, and producing documents, slides, and spreadsheets.

On visual and agentic evaluations reported at launch, Sonnet 5.5 scores 61.6% on Chartography, a chart recognition test, compared with 15.6% for Claude Sonnet 5, and 80.1% on OSWorld 2.1, a computer use benchmark measuring screenshot driven control of a desktop environment, compared with 57.0% for Sonnet 5. It reports 70.6% on Terminal-Bench 4.0 for agentic coding. Anthropic describes it as the first Sonnet model able to complete Pokemon Red from screenshots alone, and it generates output more than 30% faster than Sonnet 5 while using fewer tokens for equivalent work.

SAM 3

Released on November 19th, 2025, Segment Anything 3 (SAM 3) is a zero-shot image segmentation model that “detects, segments, and tracks objects in images and videos based on concept prompts.” This model was developed by Meta as the third model in the Segment Anything series.

Unlike its previous SAM models (Segment Anything and Segment Anything 2), you can provide SAM 3 with the prompt “shipping container” and it will generate precise segmentation masks for all shipping containers in an image. SAM 3 generates segmentation masks that correspond to the location of the objects found with a text prompt.

Frequently Asked Questions

SAM 3 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Claude Sonnet 5.5 is released under Proprietary, while SAM 3 uses Custom. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.

Yes. The comparison demo on this page runs both models on the same image side by side for object detection in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.