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Gemini 3.5 Flash-Lite vs GPT-5.4 Mini

Compare Gemini 3.5 Flash-Lite and GPT-5.4 Mini side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, Object Detection, and OCR.

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GoogleGemini 3.5 Flash-Lite
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OpenAIGPT-5.4 Mini
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Models in this comparison

Gemini 3.5 Flash-Lite vs GPT-5.4 Mini on Vision Evals

Gemini 3.5 Flash-Lite scores higher on 3 of the six Vision Evals tasks.

The widest gap is Object Detection, where Gemini 3.5 Flash-Lite leads 57.5% to 16.1%.

Overall, Gemini 3.5 Flash-Lite averages 69.6% (#14 of 25) against 63.5% (#23 of 25) for GPT-5.4 Mini.

Gemini 3.5 Flash-Lite is both cheaper ($0.0014 vs $0.0030 per sample) and faster (2.7s vs 5.3s per sample).

Gemini 3.5 Flash-LiteGPT-5.4 Mini

Gemini 3.5 Flash-Lite vs GPT-5.4 Mini Comparison Table

Evals updated August 6, 2026Pricing updated August 11, 2026

PropertyGemini 3.5 Flash-LiteGPT-5.4 Mini
OrganizationGoogleOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Mar 2026
Context Window1.0M400K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.300$0.750
Output $/1M$2.50$4.50
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Video Classification
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
69.6%
63.5%
Avg cost / sample$0.0014$0.0030
Avg speed / sample2.70s5.35s
By task
Object Detection
57.5%
$0.0023
16.1%
$0.0044
Counting
52.7%
$0.0007
60.8%
$0.0019
Identification
81.3%
$0.0004
78.1%
$0.0013
OCR
87.4%
$0.0011
88.1%
$0.0042
Data Extraction
90.7%
$0.0004
82.5%
$0.0014
Reasoning (low)
48.3%
$0.0012
55.6%
$0.0023
Reasoning (high)
68.9%
$0.0042
62.9%
$0.0081

Gemini 3.5 Flash-Lite vs GPT-5.4 Mini: Overview

Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is a natively multimodal reasoning model developed by Google DeepMind, released on July 21, 2026 as part of the Gemini 3.5 model family. It is the fastest model in the 3.5 series, designed for both low-latency tasks and high-throughput production workloads such as agentic search, document processing, receipt translation, and large-scale data extraction. The model accepts text, images, audio, and video as inputs, with a context window of up to 1 million tokens, and produces text output. It supports configurable thinking levels, allowing developers to tune the balance between response quality, cost, and latency depending on workload requirements.

On agentic and coding benchmarks, Gemini 3.5 Flash-Lite significantly outperforms its predecessor, Gemini 3.1 Flash-Lite, including on Terminal-Bench 2.1 (54% vs. 31%), GDM-MRCR v2 long-context (72.2% vs. 60.1%), and real-world task execution as measured by GDPval-AA v2 (1140 vs. 642). It also surpasses Gemini 3 Flash on SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 65.1%). According to the Artificial Analysis Index, the model generates output at approximately 350 tokens per second. It is built on the Gemini 3.5 Flash foundation and is evaluated across reasoning, coding, multimodal understanding, multilingual performance, and long-context tasks. The model is developed under Google's Frontier Safety Framework.

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 3.5 Flash-Lite performed slightly better overall. The two split the six vision tasks 3 to 3, but Gemini 3.5 Flash-Lite averages 69.6% (#14 of 25) against 63.5% (#23 of 25) 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, Gemini 3.5 Flash-Lite leads with 57.5% against 16.1%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.5 Flash-Lite is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0014 per sample against $0.0030. Gemini 3.5 Flash-Lite is priced at $0.30 per 1M input tokens and $2.50 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.

Gemini 3.5 Flash-Lite is faster. Across Roboflow's Vision Evals it averaged 2.7s per inference against 5.3s. 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.