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Claude Sonnet 5 vs Gemini 3.6 Flash

Compare Claude Sonnet 5 and Gemini 3.6 Flash side-by-side. See how these vision models stack up in Object Detection, Open Prompt, OCR, Classification, and Image Captioning.

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AnthropicClaude Sonnet 5
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GoogleGemini 3.6 Flash
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Models in this comparison

Claude Sonnet 5 vs Gemini 3.6 Flash on Vision Evals

Gemini 3.6 Flash scores higher on all five Vision Evals tasks.

The widest gap is Reasoning, where Gemini 3.6 Flash leads 77.7% to 43.0%.

Overall, Claude Sonnet 5 averages 55.3% (#47 of 63) against 77.1% (#11 of 63) for Gemini 3.6 Flash.

Gemini 3.6 Flash is cheaper ($0.0033 vs $0.0074 per sample), while Claude Sonnet 5 is faster (5.9s vs 10.4s per sample).

Claude Sonnet 5Gemini 3.6 Flash

Claude Sonnet 5 vs Gemini 3.6 Flash Comparison Table

Evals updated October 13, 2026Pricing updated October 20, 2026

PropertyClaude Sonnet 5Gemini 3.6 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2026Jul 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$0.750
Output $/1M$10.00$3.75
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Video ClassificationNot listedSupported
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
55.3%
77.1%
Avg cost / sample$0.0074$0.0033
Avg speed / sample5.86s10.43s
By task
Object Detection (low)
36.1%
$0.011
57.1%
±1.7, Mean of 3 runs, range 55.9 to 59.4
$0.0041
Object Detection (high)–
70.7%
±0.4, Mean of 3 runs, range 70.3 to 71.2
$0.0093
Counting (low)
56.8%
$0.0030
80.2%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0034
Counting (high)–
79.3%
±2.7, Mean of 3 runs, range 77.0 to 82.4
$0.0089
Identification (low)
81.3%
$0.0027
99.0%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0015
Identification (high)–
100.0%
±0.0, Mean of 3 runs, range 100.0 to 100.0
$0.0033
OCR (low)
59.4%
$0.0078
71.8%
$0.0030
by category
Single value
52.2%
Transcription
88.6%
Structured JSON
78.3%
Text localization
13.1%
Single value
68.3%
Transcription
89.4%
Structured JSON
82.9%
Text localization
42.5%
OCR (high)
59.5%
$0.015
77.4%
$0.014
by category
Single value
54.8%
Transcription
88.3%
Structured JSON
76.6%
Text localization
11.6%
Single value
68.7%
Transcription
90.3%
Structured JSON
89.3%
Text localization
62.1%
Reasoning (low)
43.0%
$0.0032
77.7%
±2.0, Mean of 3 runs, range 76.2 to 80.1
$0.0031
Reasoning (high)
43.0%
$0.0043
81.0%
±2.0, Mean of 3 runs, range 79.5 to 83.4
$0.0091

Claude Sonnet 5 vs Gemini 3.6 Flash: Overview

Claude Sonnet 5

Claude Sonnet 5 is a mid-tier large language model from Anthropic, released on June 30, 2026, as the latest model in the Sonnet series and a direct successor to Claude Sonnet 4.6. It is a hybrid reasoning model designed primarily for agentic workflows, software coding, and professional tasks. The model features a 1 million token context window, a 128k maximum output token limit, and runs adaptive thinking by default, giving API users fine-grained control over reasoning effort across five levels (low, medium, high, max, and extra-high). It uses an updated tokenizer shared with Opus 4.7 and later models, which produces approximately 30% more tokens for equivalent text compared to earlier Claude models. On benchmarks, Sonnet 5 scores 63.2% on agentic coding and 81.2% on OSWorld, narrowing the gap with Opus 4.8 while remaining at Sonnet-tier pricing.

The model supports text and image input with text output, and accepts tools including browsers and terminals for autonomous multi-step task execution. Anthropic's safety evaluations report that Sonnet 5 shows a lower rate of undesirable behaviors than Sonnet 4.6 and is generally safer in agentic contexts, with improved resistance to prompt injection and reduced sycophancy. Cybersecurity safeguards equivalent to those on Opus 4.7 and 4.8 are active, though Anthropic notes the model was not deliberately trained on cybersecurity tasks. The model is proprietary and API-only, with no open weights.

Gemini 3.6 Flash

Gemini 3.6 Flash is a multimodal language model from Google DeepMind, positioned as the workhorse tier in the Gemini 3.x family. It accepts text, image, video, audio, and PDF inputs with a 1 million token context window and produces up to 64,000 output tokens. The model builds directly on Gemini 3.5 Flash, incorporating developer and customer feedback to improve token efficiency, coding quality, and knowledge work performance. According to the Artificial Analysis Index, it consumes 17% fewer output tokens than its predecessor, and on some benchmarks such as DeepSWE, token reduction reaches up to 65%. It supports function calling, structured output, search as a tool, and code execution, and includes computer use as a built-in capability in the Gemini API and Gemini Enterprise.

On coding benchmarks, Gemini 3.6 Flash scores 49% on DeepSWE versus 37% for 3.5 Flash, and 63.9% on MLE Bench versus 49.7%. Computer use performance on OSWorld-Verified improves from 78.4% to 83%, and knowledge work scores on GDPval-AA v2 rise from 1349 to 1421. The model carries a knowledge cutoff of March 2026 and ships with enhanced Frontier Safety safeguards covering chemical, biological, radiological, nuclear, and cyber offense domains, with training to minimize refusals for beneficial uses. It is a proprietary, closed-weights model available in preview through the Gemini API via Google AI Studio, Android Studio, Google Antigravity, Gemini Enterprise, and the Gemini app.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.6 Flash performed better. It scores higher on all five vision tasks and averages 77.1% (#11 of 63) against 55.3% (#47 of 63) for Claude Sonnet 5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

No. On the Vision Evals Reasoning benchmark at low effort, Gemini 3.6 Flash leads with 77.7% against 43.0%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.6 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0033 per sample against $0.0074. Claude Sonnet 5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output; Gemini 3.6 Flash is priced at $0.75 per 1M input tokens and $3.75 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Claude Sonnet 5 is faster. Across Roboflow's Vision Evals it averaged 5.9s per inference against 10.4s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.

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