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Gemini 3.5 Flash vs Gemini 3.7 Flash

Compare Gemini 3.5 Flash and Gemini 3.7 Flash side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, OCR, and Classification.

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GoogleGemini 3.5 Flash
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Models in this comparison

Gemini 3.5 Flash vs Gemini 3.7 Flash on Vision Evals

Gemini 3.5 Flash scores higher on 4 of the six Vision Evals tasks.

The widest gap is OCR, where Gemini 3.5 Flash leads 91.1% to 86.9%.

Overall, Gemini 3.5 Flash averages 86.6% (#1 of 30) against 84.6% (#2 of 30) for Gemini 3.7 Flash.

Gemini 3.7 Flash is cheaper ($0.0016 vs $0.011 per sample), while Gemini 3.5 Flash is faster (5.8s vs 10.0s per sample).

Gemini 3.5 FlashGemini 3.7 Flash

Gemini 3.5 Flash vs Gemini 3.7 Flash Comparison Table

Evals updated August 14, 2026Pricing updated August 15, 2026

PropertyGemini 3.5 FlashGemini 3.7 Flash
OrganizationGoogleGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2026Aug 2026
Context Window1.0M1.0M
ParametersUndisclosed
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$1.50$0.375
Output $/1M$9.00$1.88
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
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
86.6%
84.6%
Avg cost / sample$0.011$0.0016
Avg speed / sample5.82s9.97s
By task
Object Detection
68.7%
$0.016
69.4%
$0.0024
Counting
81.1%
$0.0075
77.0%
$0.0013
Identification
100.0%
$0.0042
96.9%
$0.0007
OCR
91.1%
$0.016
86.9%
$0.0014
Data Extraction
94.8%
$0.0037
94.8%
$0.0007
Reasoning (low)
84.1%
$0.0080
82.8%
$0.0011
Reasoning (high)
82.8%
$0.017
82.1%
$0.0026

Gemini 3.5 Flash vs Gemini 3.7 Flash: Overview

Gemini 3.5 Flash

Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.

Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.

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.