Gemini 2.5 Flash vs Gemini 3 Flash
Compare Gemini 2.5 Flash and Gemini 3 Flash side-by-side. See how these vision models stack up in Open Prompt, OCR, Classification, Image Captioning, and Object Detection.
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Gemini 2.5 Flash vs Gemini 3 Flash: Overview
Gemini 2.5 Flash, released on June 17, 2025, is Google DeepMind’s production-ready, efficiency-focused model in the Gemini 2.5 family. It is multimodal, accepting text, images, video, and audio as inputs, with text as the primary output format. The model supports 1 million input tokens and up to 65K output tokens, enabling it to process very large contexts such as books, long video transcripts, or extensive datasets. Its training knowledge extends to January 2025.
Designed as a price-performance leader, Gemini 2.5 Flash balances speed and reasoning power, making it suitable for everyday enterprise and developer use cases without the higher latency and cost of Pro models. It supports advanced workflows like function calling, code execution, search grounding, URL context ingestion, and structured outputs. While efficient and scalable, output length is still limited compared to its input capacity, and multimodal outputs (e.g. image or audio generation) remain restricted to specialized or preview variants.
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.
Gemini 2.5 Flash vs Gemini 3 Flash Comparison Table
| Property | Gemini 2.5 Flash | Gemini 3 Flash |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jul 2025 | Dec 2025 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.300 | $0.500 |
| Output $/1M | $2.50 | $3.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Overall Score | 55.22% | 74.63% |
| Avg Response Time | 24.91s | 9.85s |
| Median input tokensincl. image tokens | 294 | 1.1K |
| Median output tokens | 171 | 290 |
| Est. cost / taskon this benchmark | $0.0005 | $0.0014 |
| Defect Detection | 60%(9/15) | 73.3%(11/15) |
| Document Understanding | 88.9%(8/9) | 88.9%(8/9) |
| Object Counting | 0%(0/10) | 30%(3/10) |
| Object Understanding | 71.4%(10/14) | 85.7%(12/14) |
| Spatial Understanding | 52.6%(10/19) | 84.2%(16/19) |
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