Roboflow

Gemini 3.8 Flash vs GPT-5.4 Mini

Compare Gemini 3.8 Flash and GPT-5.4 Mini side-by-side. See how these vision models stack up in Object Detection, Image Captioning, OCR, Classification, and Open Prompt.

Compare Gemini 3.8 Flash vs GPT-5.4 Mini 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
GoogleGemini 3.8 Flash
Run to compare this model.
OpenAIGPT-5.4 Mini
Run to compare this model.

Models in this comparison

Gemini 3.8 Flash vs GPT-5.4 Mini on Vision Evals

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

The widest gap is Object Detection, where Gemini 3.8 Flash leads 68.1% to 15.8%.

Overall, Gemini 3.8 Flash averages 79.8% (#7 of 63) against 53.2% (#51 of 63) for GPT-5.4 Mini.

GPT-5.4 Mini is both cheaper ($0.0034 vs $0.0045 per sample) and faster (5.5s vs 12.8s per sample).

Gemini 3.8 FlashGPT-5.4 Mini

Gemini 3.8 Flash vs GPT-5.4 Mini Comparison Table

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

PropertyGemini 3.8 FlashGPT-5.4 Mini
OrganizationGoogleOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateSep 2026Mar 2026
Context Window1.0M400K
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$0.825$0.750
Output $/1M$4.13$4.50
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
79.8%
53.2%
Avg cost / sample$0.0045$0.0034
Avg speed / sample12.76s5.51s
By task
Object Detection (low)
68.1%
±0.8, Mean of 3 runs, range 67.3 to 69.0
$0.0045
15.8%
±0.4, Mean of 3 runs, range 15.3 to 16.1
$0.0044
Object Detection (high)
74.8%
±1.1, Mean of 3 runs, range 73.4 to 75.6
$0.023
16.6%
±0.8, Mean of 3 runs, range 15.8 to 17.4
$0.030
Counting (low)
78.8%
±2.7, Mean of 3 runs, range 75.7 to 81.1
$0.0040
58.6%
±2.0, Mean of 3 runs, range 56.8 to 60.8
$0.0019
Counting (high)
79.3%
±1.4, Mean of 3 runs, range 78.4 to 81.1
$0.027
64.9%
±2.0, Mean of 3 runs, range 63.5 to 67.6
$0.0073
Identification (low)
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0016
83.3%
±1.6, Mean of 3 runs, range 81.3 to 84.4
$0.0013
Identification (high)
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0037
82.3%
±3.1, Mean of 3 runs, range 78.1 to 84.4
$0.0055
OCR (low)
72.8%
$0.0049
51.1%
$0.0035
by category
Single value
73.5%
Transcription
91.3%
Structured JSON
86.1%
Text localization
26.4%
Single value
41.3%
Transcription
77.3%
Structured JSON
73.6%
Text localization
4.1%
OCR (high)
78.7%
$0.039
55.8%
$0.027
by category
Single value
70.9%
Transcription
94.1%
Structured JSON
90.9%
Text localization
58.6%
Single value
47.0%
Transcription
78.5%
Structured JSON
79.0%
Text localization
6.1%
Reasoning (low)
81.2%
±0.3, Mean of 3 runs, range 80.8 to 81.5
$0.0038
57.0%
±3.3, Mean of 3 runs, range 54.3 to 60.9
$0.0022
Reasoning (high)
84.5%
±1.0, Mean of 3 runs, range 83.4 to 85.4
$0.023
64.0%
±1.3, Mean of 3 runs, range 62.9 to 65.6
$0.0096

Gemini 3.8 Flash vs GPT-5.4 Mini: Overview

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.

GPT-5.4 Mini

GPT-5.4 mini is a fast, cost-efficient model developed by OpenAI and released on March 17, 2026, optimized for high-throughput workloads and subagent orchestration. It supports text and image inputs within a 400,000-token context window, making it ideal for processing extensive visual datasets and large codebases in a single request. Designed for low-latency production environments, the model integrates with key API features including function calling, web search, and tool-based computer use, allowing it to assist in automated workflows that require navigating digital interfaces.

Compared to the previous GPT-5 mini, this version runs more than twice as fast while approaching the performance levels of the flagship GPT-5.4 on reasoning and coding benchmarks. While the larger GPT-5.4 introduces native, state-of-the-art computer-use capabilities, GPT-5.4 mini provides a scalable alternative for interpreting screenshots and reasoning over dense UI layouts. For vision tasks on Playground, it excels at extracting structured information from visual documents and assisting in agentic tasks that involve real-time interpretation of software interfaces alongside text.

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 53.2% (#51 of 63) for GPT-5.4 Mini. 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, Gemini 3.8 Flash leads with 68.1% against 15.8%. This is the widest gap between the two models across the benchmark's tasks.

GPT-5.4 Mini is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0034 per sample against $0.0045. Gemini 3.8 Flash is priced at $0.83 per 1M input tokens and $4.13 per 1M output; GPT-5.4 Mini is priced at $0.75 per 1M input tokens and $4.50 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

GPT-5.4 Mini is faster. Across Roboflow's Vision Evals it averaged 5.5s 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 image captioning in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.