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Gemini 3.5 Flash-Lite vs GPT-5 Mini

Compare Gemini 3.5 Flash-Lite and GPT-5 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 Mini
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Gemini 3.5 Flash-Lite vs GPT-5 Mini Comparison Table

Evals updated July 10, 2026Pricing updated July 21, 2026

PropertyGemini 3.5 Flash-LiteGPT-5 Mini
OrganizationGoogleOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Aug 2025
Context Window1.0M400K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.250
Output $/1M$2.00
Vision Tasks
CaptioningDemoDemo
ClassificationDemoDemo
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Document Question Answering
Multi-Label Classification
Video Classification
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Real-Time Vision

Gemini 3.5 Flash-Lite vs GPT-5 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 Mini

GPT-5 Mini, released by OpenAI on August 7, 2025, is a mid-tier variant of the GPT-5 family that balances cost, speed, and capability. It is multimodal, supporting both text and image inputs, and offers a substantial input context window of ~400,000 tokens with output lengths up to ~128,000 tokens. While less powerful than the full GPT-5, it inherits its safety tuning, instruction-following improvements, and multimodal reasoning, making it a practical choice for developers who need large context handling without the expense of premium models.

GPT-5 Mini is optimized for affordability while retaining strong reasoning performance. Benchmarks show it outperforming earlier models such as GPT-4o on many multimodal and medical VQA tasks, though it lags behind GPT-5 on the most complex problems. Ideal use cases include prototyping, scalable content generation, document analysis, and mid-range reasoning tasks where efficiency and context capacity matter more than top-tier accuracy.