Gemini 3 Flash vs GPT-4o mini
Compare Gemini 3 Flash and GPT-4o mini side-by-side. See how these vision models stack up in Object Detection, Classification, Open Prompt, OCR, and Image Captioning.
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GPT-4o mini is deprecated and can no longer be run. Details and evals are still available on its model page.
Models in this comparison
Gemini 3 Flash vs GPT-4o mini: Overview
Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.
The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.
GPT-4o mini, launched by OpenAI in July 2024, is a lightweight, cost-efficient variant of GPT-4o designed for developers who need strong multimodal reasoning at scale. It supports text and vision inputs (with audio/video support planned) and offers a 128,000-token input context window with outputs up to ~16,000 tokens. Like GPT-4o, it has a knowledge cutoff of October 2023 and integrates the same safety mitigations against misuse and prompt attacks.
GPT-4o mini is significantly cheaper than full GPT-4o while outperforming older models such as GPT-3.5 Turbo. It achieves around 82% on MMLU, reflecting solid reasoning, math, and coding capabilities despite its efficiency focus. The model replaced GPT-3.5 Turbo as the default in ChatGPT for many users, making it widely accessible for everyday conversational AI, educational tools, content generation, and scalable multimodal applications where affordability and speed are priorities.
Gemini 3 Flash vs GPT-4o mini Comparison Table
| Property | Gemini 3 Flash | GPT-4o mini |
|---|---|---|
| Organization | OpenAI | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Jul 2024 |
| Context Window | 1.0M | 128K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $0.150 |
| Output $/1M | $3.00 | $0.600 |
| Vision Tasks | ||
| Captioning | Demo | |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 74.63% | |
| Avg Response Time | 9.85s | |
| Median input tokensincl. image tokens | 1.1K | |
| Median output tokens | 290 | |
| Est. cost / taskon this benchmark | $0.0014 | |
| Defect Detection | 73.3%(11/15) | |
| Document Understanding | 88.9%(8/9) | |
| Object Counting | 30%(3/10) | |
| Object Understanding | 85.7%(12/14) | |
| Spatial Understanding | 84.2%(16/19) | |
| OCR | ||
| Overall Score | 93.01% | |
| Avg Response Time | 12.40s | |
| Median input tokensincl. image tokens | 1.1K | |
| Median output tokens | 160 | |
| Est. cost / taskon this benchmark | $0.0010 | |
| Focused Scene OCR | 94.9%(94/99) | |
| Handwritten Math | 100%(10/10) | |
| License Plate Recognition | 100%(30/30) | |
| Text Recognition | 86.7%(26/30) | |
| VQA & Extraction | 88.3%(53/60) | |
Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology