Roboflow

Claude Opus 5.5 vs Gemini 3.7 Flash

Compare Claude Opus 5.5 and Gemini 3.7 Flash side-by-side.

Compare Claude Opus 5.5 vs Gemini 3.7 Flash live

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

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

Models in this comparison

Claude Opus 5.5 vs Gemini 3.7 Flash on Vision Evals

Claude Opus 5.5 scores higher on 3 of the six Vision Evals tasks.

The widest gap is Object Detection, where Claude Opus 5.5 leads 74.4% to 70.5%.

Overall, Claude Opus 5.5 averages 85.5% (#3 of 57) against 85.2% (#4 of 57) for Gemini 3.7 Flash.

Gemini 3.7 Flash is cheaper ($0.0031 vs $0.014 per sample), while Claude Opus 5.5 is faster (12.8s vs 16.5s per sample).

Claude Opus 5.5Gemini 3.7 Flash

Claude Opus 5.5 vs Gemini 3.7 Flash Comparison Table

Evals updated September 22, 2026Pricing updated September 22, 2026

PropertyClaude Opus 5.5Gemini 3.7 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Aug 2026
Context Window1.0M1.0M
ParametersUndisclosed
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.750
Output $/1M$3.75
Vision Tasks
CaptioningDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
85.5%
85.2%
Avg cost / sample$0.014$0.0031
Avg speed / sample12.76s16.50s
By task
Object Detection (low)
74.4%
±0.5, Mean of 3 runs, range 73.9 to 74.8
$0.022
70.5%
±1.1, Mean of 3 runs, range 69.4 to 71.5
$0.0047
Object Detection (high)
76.8%
±1.2, Mean of 3 runs, range 75.4 to 77.8
$0.030
74.3%
±0.8, Mean of 3 runs, range 73.3 to 75.0
$0.0089
Counting (low)
80.6%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0081
78.4%
±1.4, Mean of 3 runs, range 77.0 to 79.7
$0.0025
Counting (high)
82.0%
±2.0, Mean of 3 runs, range 79.7 to 83.8
$0.0098
79.3%
±2.0, Mean of 3 runs, range 77.0 to 81.1
$0.0056
Identification (low)
93.8%
±0.0, Mean of 3 runs, range 93.8 to 93.8
$0.0058
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0013
Identification (high)
95.8%
±1.6, Mean of 3 runs, range 93.8 to 96.9
$0.0067
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0021
OCR (low)
87.8%
±0.6, Mean of 3 runs, range 87.0 to 88.2
$0.017
88.2%
±1.6, Mean of 3 runs, range 86.9 to 90.0
$0.0027
OCR (high)
87.2%
±0.6, Mean of 3 runs, range 86.5 to 87.8
$0.024
89.0%
±0.8, Mean of 3 runs, range 88.3 to 89.9
$0.0093
Data Extraction (low)
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.0066
96.2%
±0.5, Mean of 3 runs, range 95.9 to 96.9
$0.0014
Data Extraction (high)
93.5%
±0.5, Mean of 3 runs, range 92.8 to 93.8
$0.0075
95.9%
±0.0, Mean of 3 runs, range 95.9 to 95.9
$0.0023
Reasoning (low)
83.0%
±1.0, Mean of 3 runs, range 82.1 to 84.1
$0.0090
80.8%
±2.0, Mean of 3 runs, range 78.8 to 82.8
$0.0022
Reasoning (high)
85.9%
±2.6, Mean of 3 runs, range 82.8 to 88.1
$0.011
81.9%
±1.3, Mean of 3 runs, range 80.1 to 82.8
$0.0050

Claude Opus 5.5 vs Gemini 3.7 Flash: Overview

Claude Opus 5.5

Claude Opus 5.5 is a proprietary multimodal reasoning model from Anthropic and the first entry in the Claude 5.5 family. It accepts interleaved text and image input and returns text, with a one million token context window and up to 128,000 output tokens per response. Adaptive thinking is always enabled on this model and cannot be disabled; thinking depth is instead governed by an effort parameter with five levels, where medium is the default, a change from the high default used by Claude Opus 5 and earlier Opus models. Anthropic reports a knowledge cutoff of June 2026.

On the visual side, Anthropic characterizes Opus 5.5 as its strongest Opus release for vision and computer use, describing improved reading of dense documents, charts, screenshots, and diagrams for document extraction and visual analysis tasks. Published results include 89.0% on Chartography with tools and 81.8% on OSWorld 2.0 under partial credit scoring, alongside 48.7% under strict scoring reported in the system card. The accompanying system card states that Opus 5.5 scored higher than Opus 5 on every evaluation in its capability summary, with the largest gains concentrated in agentic coding, visual reasoning, computer use, and long-horizon knowledge work. The model ships with safety classifiers covering biology and cybersecurity that can route blocked requests to earlier Claude models.

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, Claude Opus 5.5 performed slightly better overall. The two split the six vision tasks 3 to 3, but Claude Opus 5.5 averages 85.5% (#3 of 57) against 85.2% (#4 of 57) for Gemini 3.7 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals Object Detection benchmark at low effort, Claude Opus 5.5 leads with 74.4% against 70.5%. 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 $0.014. Actual costs depend on your image sizes, prompts, and output length.

Claude Opus 5.5 is faster. Across Roboflow's Vision Evals it averaged 12.8s per inference against 16.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.