Gemini 2.5 Pro vs Gemini 3 Flash
Compare Gemini 2.5 Pro and Gemini 3 Flash side-by-side. See how these vision models stack up in Object Detection, Open Prompt, Classification, OCR, and Image Captioning.
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Gemini 2.5 Pro vs Gemini 3 Flash on Vision Evals
Gemini 3 Flash scores higher on 4 of the six Vision Evals tasks.
The widest gap is Reasoning, where Gemini 3 Flash leads 78.3% to 60.9%.
Overall, Gemini 2.5 Pro averages 67.9% (#9 of 16) against 77.2% (#4 of 16) for Gemini 3 Flash.
Gemini 3 Flash is both cheaper ($0.0017 vs $0.0036 per sample) and faster (3.9s vs 4.7s per sample).
Gemini 2.5 Pro vs Gemini 3 Flash Comparison Table
Evals updated July 10, 2026Pricing updated July 20, 2026
| Property | Gemini 2.5 Pro | Gemini 3 Flash |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 2025 | Dec 2025 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | $0.500 |
| Output $/1M | $10.00 | $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 Evalsground-truth scores across 6 vision tasks | ||
| Overall | 67.9% | 77.2% |
| Object Detection | 26.4% | 39.3% |
| Counting | 52.7% | 67.6% |
| Identification | 93.8% | 93.8% |
| OCR | 88.8% | 87.6% |
| Data Extraction | 84.5% | 96.9% |
| Reasoning | 60.9% | 78.3% |
| Avg cost / sample | $0.0036 | $0.0017 |
| Avg speed / sample | 4.7s | 3.9s |
Gemini 2.5 Pro vs Gemini 3 Flash: Overview
Gemini 2.5 Pro, released on June 17, 2025, is Google DeepMind’s most capable model in the Gemini 2.5 family, optimized for deep reasoning, coding, and complex multimodal tasks. It accepts text, images, audio, video, and PDFs as input and outputs text. The model supports 1 million input tokens with an output capacity of up to 65K tokens, enabling large-scale comprehension of datasets, codebases, and technical documents. Its training knowledge extends to January 2025.
Pro outperforms earlier Gemini 2.0 models across benchmarks, including agentic coding tasks where it achieved ~63.8% on SWE-Bench Verified. It supports structured outputs, function calling, code execution, search grounding, and URL context, making it well-suited for enterprise, STEM, and developer workflows. However, it does not currently support image or audio generation in its stable release, and its higher computational cost and latency make it less efficient than Flash or Flash-Lite. It is available via the Gemini API, Google AI Studio, and Vertex AI.
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.