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Gemini 3.6 Flash vs Gemini 3.8 Flash

Compare Gemini 3.6 Flash and Gemini 3.8 Flash side-by-side. See how these vision models stack up in Open Prompt, Classification, Image Captioning, OCR, and Object Detection.

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GoogleGemini 3.6 Flash
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Models in this comparison

Gemini 3.6 Flash vs Gemini 3.8 Flash on Vision Evals

Gemini 3.8 Flash scores higher on 3 of the five Vision Evals tasks.

The widest gap is Object Detection, where Gemini 3.8 Flash leads 68.1% to 57.1%.

Overall, Gemini 3.6 Flash averages 77.1% (#11 of 63) against 79.8% (#7 of 63) for Gemini 3.8 Flash.

Gemini 3.6 Flash is both cheaper ($0.0033 vs $0.0045 per sample) and faster (10.4s vs 12.8s per sample).

Gemini 3.6 FlashGemini 3.8 Flash

Gemini 3.6 Flash vs Gemini 3.8 Flash Comparison Table

Evals updated October 13, 2026Pricing updated October 17, 2026

PropertyGemini 3.6 FlashGemini 3.8 Flash
OrganizationGoogleGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Sep 2026
Context Window1.0M1.0M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$0.750$0.825
Output $/1M$3.75$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
Video ClassificationSupportedNot listed
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
77.1%
79.8%
Avg cost / sample$0.0033$0.0045
Avg speed / sample10.43s12.76s
By task
Object Detection (low)
57.1%
±1.7, Mean of 3 runs, range 55.9 to 59.4
$0.0041
68.1%
±0.8, Mean of 3 runs, range 67.3 to 69.0
$0.0045
Object Detection (high)
70.7%
±0.4, Mean of 3 runs, range 70.3 to 71.2
$0.0093
74.8%
±1.1, Mean of 3 runs, range 73.4 to 75.6
$0.023
Counting (low)
80.2%
±2.0, Mean of 3 runs, range 78.4 to 82.4
$0.0034
78.8%
±2.7, Mean of 3 runs, range 75.7 to 81.1
$0.0040
Counting (high)
79.3%
±2.7, Mean of 3 runs, range 77.0 to 82.4
$0.0089
79.3%
±1.4, Mean of 3 runs, range 78.4 to 81.1
$0.027
Identification (low)
99.0%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0015
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0016
Identification (high)
100.0%
±0.0, Mean of 3 runs, range 100.0 to 100.0
$0.0033
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0037
OCR (low)
71.8%
$0.0030
72.8%
$0.0049
by category
Single value
68.3%
Transcription
89.4%
Structured JSON
82.9%
Text localization
42.5%
Single value
73.5%
Transcription
91.3%
Structured JSON
86.1%
Text localization
26.4%
OCR (high)
77.4%
$0.014
78.7%
$0.039
by category
Single value
68.7%
Transcription
90.3%
Structured JSON
89.3%
Text localization
62.1%
Single value
70.9%
Transcription
94.1%
Structured JSON
90.9%
Text localization
58.6%
Reasoning (low)
77.7%
±2.0, Mean of 3 runs, range 76.2 to 80.1
$0.0031
81.2%
±0.3, Mean of 3 runs, range 80.8 to 81.5
$0.0038
Reasoning (high)
81.0%
±2.0, Mean of 3 runs, range 79.5 to 83.4
$0.0091
84.5%
±1.0, Mean of 3 runs, range 83.4 to 85.4
$0.023

Gemini 3.6 Flash vs Gemini 3.8 Flash: Overview

Gemini 3.6 Flash

Gemini 3.6 Flash is a multimodal language model from Google DeepMind, positioned as the workhorse tier in the Gemini 3.x family. It accepts text, image, video, audio, and PDF inputs with a 1 million token context window and produces up to 64,000 output tokens. The model builds directly on Gemini 3.5 Flash, incorporating developer and customer feedback to improve token efficiency, coding quality, and knowledge work performance. According to the Artificial Analysis Index, it consumes 17% fewer output tokens than its predecessor, and on some benchmarks such as DeepSWE, token reduction reaches up to 65%. It supports function calling, structured output, search as a tool, and code execution, and includes computer use as a built-in capability in the Gemini API and Gemini Enterprise.

On coding benchmarks, Gemini 3.6 Flash scores 49% on DeepSWE versus 37% for 3.5 Flash, and 63.9% on MLE Bench versus 49.7%. Computer use performance on OSWorld-Verified improves from 78.4% to 83%, and knowledge work scores on GDPval-AA v2 rise from 1349 to 1421. The model carries a knowledge cutoff of March 2026 and ships with enhanced Frontier Safety safeguards covering chemical, biological, radiological, nuclear, and cyber offense domains, with training to minimize refusals for beneficial uses. It is a proprietary, closed-weights model available in preview through the Gemini API via Google AI Studio, Android Studio, Google Antigravity, Gemini Enterprise, and the Gemini app.

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 3 of the five vision tasks and averages 79.8% (#7 of 63) against 77.1% (#11 of 63) for Gemini 3.6 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

No. On the Vision Evals Object Detection benchmark at low effort, Gemini 3.8 Flash leads with 68.1% against 57.1%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.6 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0033 per sample against $0.0045. Gemini 3.6 Flash is priced at $0.75 per 1M input tokens and $3.75 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.

Gemini 3.6 Flash is faster. Across Roboflow's Vision Evals it averaged 10.4s 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 open prompts and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.