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Gemini 3.1 Pro vs Gemini 3.7 Flash

Compare Gemini 3.1 Pro and Gemini 3.7 Flash side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, OCR, and Object Detection.

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GoogleGemini 3.1 Pro
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GoogleGemini 3.7 Flash
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Models in this comparison

Gemini 3.1 Pro vs Gemini 3.7 Flash on Vision Evals

Gemini 3.7 Flash scores higher on 4 of the six Vision Evals tasks.

The widest gap is Reasoning, where Gemini 3.7 Flash leads 80.8% to 72.2%.

Overall, Gemini 3.1 Pro averages 83.3% (#9 of 61) against 85.2% (#6 of 61) for Gemini 3.7 Flash.

Gemini 3.7 Flash is cheaper ($0.0031 vs $0.0093 per sample), while Gemini 3.1 Pro is faster (7.8s vs 16.5s per sample).

Gemini 3.1 ProGemini 3.7 Flash

Gemini 3.1 Pro vs Gemini 3.7 Flash Comparison Table

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

PropertyGemini 3.1 ProGemini 3.7 Flash
OrganizationGoogleGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateFeb 2026Aug 2026
Context Window1.0M1.0M
ParametersUndisclosed
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.00$0.750
Output $/1M$12.00$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
83.3%
85.2%
Avg cost / sample$0.0093$0.0031
Avg speed / sample7.81s16.50s
By task
Object Detection (low)
67.6%
$0.010
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)
71.6%
$0.0071
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)
100.0%
$0.0070
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)
92.6%
$0.0066
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)
95.9%
$0.0063
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)
72.2%
$0.012
80.8%
±2.0, Mean of 3 runs, range 78.8 to 82.8
$0.0022
Reasoning (high)
74.8%
$0.021
81.9%
±1.3, Mean of 3 runs, range 80.1 to 82.8
$0.0050

Gemini 3.1 Pro vs Gemini 3.7 Flash: Overview

Gemini 3.1 Pro

Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.

The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.

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 4 of the six vision tasks and averages 85.2% (#6 of 61) against 83.3% (#9 of 61) for Gemini 3.1 Pro. 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 72.2%. 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 $0.0093. Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 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.

Gemini 3.1 Pro is faster. Across Roboflow's Vision Evals it averaged 7.8s 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 image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.