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Claude Sonnet 5 vs Gemini 3.7 Flash

Compare Claude Sonnet 5 and Gemini 3.7 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 3.7 Flash
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Models in this comparison

Claude Sonnet 5 vs Gemini 3.7 Flash on Vision Evals

Gemini 3.7 Flash scores higher on 5 of the six Vision Evals tasks.

The widest gap is Reasoning, where Gemini 3.7 Flash leads 80.8% to 43.0%.

Overall, Claude Sonnet 5 averages 66.4% (#38 of 61) against 85.2% (#6 of 61) for Gemini 3.7 Flash.

Gemini 3.7 Flash is cheaper ($0.0031 vs $0.0064 per sample), while Claude Sonnet 5 is faster (4.8s vs 16.5s per sample).

Claude Sonnet 5Gemini 3.7 Flash

Claude Sonnet 5 vs Gemini 3.7 Flash Comparison Table

Evals updated September 29, 2026Pricing updated September 29, 2026

PropertyClaude Sonnet 5Gemini 3.7 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2026Aug 2026
Context Window1.0M1.0M
ParametersUndisclosed
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.00$0.750
Output $/1M$10.00$3.75
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
66.4%
85.2%
Avg cost / sample$0.0064$0.0031
Avg speed / sample4.84s16.50s
By task
Object Detection (low)
36.1%
$0.011
71.0%
±0.9, Mean of 3 runs, range 69.8 to 71.6
$0.0047
Object Detection (high)–
74.4%
±0.7, Mean of 3 runs, range 73.6 to 75.0
$0.0089
Counting (low)
56.8%
$0.0030
78.4%
±1.4, Mean of 3 runs, range 77.0 to 79.7
$0.0025
Counting (high)–
79.3%
±2.0, Mean of 3 runs, range 77.0 to 81.1
$0.0056
Identification (low)
81.3%
$0.0027
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0013
Identification (high)–
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0021
OCR (low)
91.7%
$0.0078
88.2%
±1.6, Mean of 3 runs, range 86.9 to 90.0
$0.0027
OCR (high)–
89.0%
±0.8, Mean of 3 runs, range 88.3 to 89.9
$0.0093
Data Extraction (low)
89.7%
$0.0030
96.2%
±0.5, Mean of 3 runs, range 95.9 to 96.9
$0.0014
Data Extraction (high)–
95.9%
±0.0, Mean of 3 runs, range 95.9 to 95.9
$0.0023
Reasoning (low)
43.0%
$0.0032
80.8%
±2.0, Mean of 3 runs, range 78.8 to 82.8
$0.0022
Reasoning (high)
43.0%
$0.0043
81.9%
±1.3, Mean of 3 runs, range 80.1 to 82.8
$0.0050

Claude Sonnet 5 vs Gemini 3.7 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 3.7 Flash

Gemini 3.7 Flash is a proprietary multimodal model from Google, positioned in the Flash branch of the Gemini 3 series that trades some of the capacity of the larger Pro models for lower latency and lower cost per token. It accepts interleaved text and image input alongside other modalities handled by the Gemini family and returns text, and it continues the series pattern of exposing a configurable thinking budget so that reasoning effort can be scaled up for harder problems or reduced for high throughput extraction, routing and classification work. The model is announced roughly three weeks after Gemini 3.6 Flash, part of an unusually fast iteration cadence within the Flash line.

Google reports gains concentrated in agentic coding and front end generation, citing a WebDev Arena Elo of 1588 for this release compared with 1538 for the preceding Flash model, and describes it as producing more functional layouts and more feature complete applications in fewer prompts. Weights are not published and the architecture, parameter count and training corpus are undisclosed, consistent with prior Gemini releases. Visual capability follows the Flash lineage, covering image and document understanding, chart and diagram interpretation, text recognition in images, and general visual question answering.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.7 Flash performed better. It scores higher on 5 of the six vision tasks and averages 85.2% (#6 of 61) against 66.4% (#38 of 61) 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 3.7 Flash leads with 80.8% against 43.0%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.7 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0031 per sample against $0.0064. Claude Sonnet 5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output; Gemini 3.7 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 4.8s per inference against 16.5s. 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.