Roboflow

Claude Sonnet 5 vs Gemini 3.8 Flash

Compare Claude Sonnet 5 and Gemini 3.8 Flash side-by-side. See how these vision models stack up in Object Detection, Open Prompt, OCR, Classification, and Image Captioning.

Compare Claude Sonnet 5 vs Gemini 3.8 Flash 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
Run to compare this model.
GoogleGemini 3.8 Flash
Run to compare this model.

Models in this comparison

Claude Sonnet 5 vs Gemini 3.8 Flash on Vision Evals

Gemini 3.8 Flash scores higher on all five Vision Evals tasks.

The widest gap is Reasoning, where Gemini 3.8 Flash leads 81.2% to 43.0%.

Overall, Claude Sonnet 5 averages 55.3% (#47 of 63) against 79.8% (#7 of 63) for Gemini 3.8 Flash.

Gemini 3.8 Flash is cheaper ($0.0045 vs $0.0074 per sample), while Claude Sonnet 5 is faster (5.9s vs 12.8s per sample).

Claude Sonnet 5Gemini 3.8 Flash

Claude Sonnet 5 vs Gemini 3.8 Flash Comparison Table

Evals updated October 13, 2026Pricing updated October 18, 2026

PropertyClaude Sonnet 5Gemini 3.8 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJun 2026Sep 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$0.825
Output $/1M$10.00$4.13
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
55.3%
79.8%
Avg cost / sample$0.0074$0.0045
Avg speed / sample5.86s12.76s
By task
Object Detection (low)
36.1%
$0.011
68.1%
±0.8, Mean of 3 runs, range 67.3 to 69.0
$0.0045
Object Detection (high)–
74.8%
±1.1, Mean of 3 runs, range 73.4 to 75.6
$0.023
Counting (low)
56.8%
$0.0030
78.8%
±2.7, Mean of 3 runs, range 75.7 to 81.1
$0.0040
Counting (high)–
79.3%
±1.4, Mean of 3 runs, range 78.4 to 81.1
$0.027
Identification (low)
81.3%
$0.0027
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0016
Identification (high)–
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0037
OCR (low)
59.4%
$0.0078
72.8%
$0.0049
by category
Single value
52.2%
Transcription
88.6%
Structured JSON
78.3%
Text localization
13.1%
Single value
73.5%
Transcription
91.3%
Structured JSON
86.1%
Text localization
26.4%
OCR (high)
59.5%
$0.015
78.7%
$0.039
by category
Single value
54.8%
Transcription
88.3%
Structured JSON
76.6%
Text localization
11.6%
Single value
70.9%
Transcription
94.1%
Structured JSON
90.9%
Text localization
58.6%
Reasoning (low)
43.0%
$0.0032
81.2%
±0.3, Mean of 3 runs, range 80.8 to 81.5
$0.0038
Reasoning (high)
43.0%
$0.0043
84.5%
±1.0, Mean of 3 runs, range 83.4 to 85.4
$0.023

Claude Sonnet 5 vs Gemini 3.8 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 3.8 Flash

Gemini 3.8 Flash is a natively multimodal reasoning model in Google's Gemini 3 series, positioned as the speed and cost oriented Flash tier while targeting long-horizon software engineering, autonomous agents, and enterprise workflows. It accepts text, images, video, audio, and PDF documents in a single request and returns text, with an input limit of 1,048,576 tokens and an output limit of 65,536 tokens. Thinking is configurable at low, medium, and high levels, and the model supports function calling, code execution, structured outputs, context caching, search and Maps grounding, file search, and computer use in preview. Image generation, audio generation, and the Live API are not supported.

On vision oriented evaluations the model reports 86.2% on CharXiv Reasoning for chart and figure synthesis and 87.8% on LVBench for long video understanding in agentic mode, alongside 90.8% on Terminal-Bench 2.1 and 61.6% on SWE-Bench Pro for coding. Following Gemini API conventions, it can localize objects by emitting bounding boxes as [ymin, xmin, ymax, xmax] integers normalized to a 0 to 1000 range, which supports prompt driven detection and grounding in addition to captioning, document parsing, and visual question answering. The knowledge cutoff is March 2026, though coverage in some domains reflects the January 2025 cutoff shared across the Gemini 3 family.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.8 Flash performed better. It scores higher on all five vision tasks and averages 79.8% (#7 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 3.8 Flash leads with 81.2% against 43.0%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.8 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0045 per sample against $0.0074. Claude Sonnet 5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output; Gemini 3.8 Flash is priced at $0.83 per 1M input tokens and $4.13 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 12.8s. 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.