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Claude Sonnet 5.5 vs Gemini 3.5 Flash

Compare Claude Sonnet 5.5 and Gemini 3.5 Flash side-by-side. See how these vision models stack up in Image Captioning, OCR, Classification, Object Detection, and Open Prompt.

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AnthropicClaude Sonnet 5.5
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GoogleGemini 3.5 Flash
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Models in this comparison

Claude Sonnet 5.5 vs Gemini 3.5 Flash on Vision Evals

Gemini 3.5 Flash scores higher on 4 of the five Vision Evals tasks.

The widest gap is OCR, where Gemini 3.5 Flash leads 76.7% to 66.3%.

Overall, Claude Sonnet 5.5 averages 77.6% (#9 of 62) against 81.8% (#3 of 62) for Gemini 3.5 Flash.

Claude Sonnet 5.5 is both cheaper ($0.0073 vs $0.012 per sample) and faster (8.3s vs 11.5s per sample).

Claude Sonnet 5.5Gemini 3.5 Flash

Claude Sonnet 5.5 vs Gemini 3.5 Flash Comparison Table

Evals updated October 13, 2026Pricing updated October 13, 2026

PropertyClaude Sonnet 5.5Gemini 3.5 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026May 2026
Context Window1.0M1.0M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$2.00$1.50
Output $/1M$10.00$9.00
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
77.6%
81.8%
Avg cost / sample$0.0073$0.012
Avg speed / sample8.33s11.52s
By task
Object Detection (low)
74.3%
±0.9, Mean of 3 runs, range 73.5 to 75.3
$0.0098
70.6%
±2.0, Mean of 3 runs, range 68.7 to 72.6
$0.016
Object Detection (high)
76.8%
±0.4, Mean of 3 runs, range 76.5 to 77.3
$0.014
69.8%
±1.8, Mean of 3 runs, range 67.5 to 71.1
$0.021
Counting (low)
79.3%
±0.7, Mean of 3 runs, range 78.4 to 79.7
$0.0042
80.6%
±0.7, Mean of 3 runs, range 79.7 to 81.1
$0.0075
Counting (high)
82.9%
±1.4, Mean of 3 runs, range 81.1 to 83.8
$0.0053
82.4%
±0.0, Mean of 3 runs, range 82.4 to 82.4
$0.017
Identification (low)
91.7%
±3.1, Mean of 3 runs, range 87.5 to 93.8
$0.0029
99.0%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0040
Identification (high)
90.6%
±0.0, Mean of 3 runs, range 90.6 to 90.6
$0.0033
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0068
OCR (low)
66.3%
$0.0075
76.7%
$0.013
by category
Single value
48.7%
Transcription
76.3%
Structured JSON
83.8%
Text localization
60.6%
Single value
71.7%
Transcription
90.0%
Structured JSON
86.8%
Text localization
56.2%
OCR (high)–
75.5%
$0.031
by category
Single value
69.6%
Transcription
85.4%
Structured JSON
88.1%
Text localization
53.3%
Reasoning (low)
76.4%
±0.7, Mean of 3 runs, range 75.5 to 76.8
$0.0049
82.1%
±2.0, Mean of 3 runs, range 80.1 to 84.1
$0.0082
Reasoning (high)
83.9%
±1.7, Mean of 3 runs, range 82.1 to 85.4
$0.0061
81.0%
±1.7, Mean of 3 runs, range 79.5 to 82.8
$0.018

Claude Sonnet 5.5 vs Gemini 3.5 Flash: 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.

Gemini 3.5 Flash

Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.

Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.