Gemini 2.5 Pro vs Gemini 3.1 Pro
Compare Gemini 2.5 Pro and Gemini 3.1 Pro 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 3.1 Pro: 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 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.
The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.
Gemini 2.5 Pro vs Gemini 3.1 Pro Comparison Table
| Property | Gemini 2.5 Pro | Gemini 3.1 Pro |
|---|---|---|
| Organization | ||
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 2025 | Feb 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | $2.00 |
| Output $/1M | $10.00 | $12.00 |
| 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% | ||
| Visual Understanding | ||
| Overall Score | 70.15% | 75.76% |
| Avg Response Time | 11.87s | 6.13s |
| Median input tokensincl. image tokens | 294 | 1.1K |
| Median output tokens | 565 | 11 |
| Est. cost / taskon this benchmark | $0.0060 | $0.0024 |
| Defect Detection | 73.3%(11/15) | 73.3%(11/15) |
| Document Understanding | 88.9%(8/9) | 88.9%(8/9) |
| Object Counting | 20%(2/10) | 44.4%(4/9) |
| Object Understanding | 78.6%(11/14) | 92.9%(13/14) |
| Spatial Understanding | 78.9%(15/19) | 73.7%(14/19) |
| OCR | ||
| Overall Score | 78.6% | 89.52% |
| Avg Response Time | 4.91s | 3.11s |
| Median input tokensincl. image tokens | 290 | 1.1K |
| Median output tokens | 323 | 12 |
| Est. cost / taskon this benchmark | $0.0036 | $0.0024 |
| Focused Scene OCR | 78.8%(78/99) | 94.9%(94/99) |
| Handwritten Math | 80%(8/10) | 90%(9/10) |
| License Plate Recognition | 90%(27/30) | 90%(27/30) |
| Text Recognition | 73.3%(22/30) | 86.7%(26/30) |
| VQA & Extraction | 75%(45/60) | 81.7%(49/60) |
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