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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Models in this comparison
Gemini 2.5 Pro vs Gemini 3.1 Pro on Vision Evals
Gemini 3.1 Pro scores higher on all six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.1 Pro leads 67.4% to 33.7%.
Overall, Gemini 2.5 Pro averages 66.0% (#22 of 31) against 83.1% (#4 of 31) for Gemini 3.1 Pro.
Gemini 2.5 Pro is both cheaper ($0.0050 vs $0.0093 per sample) and faster (6.1s vs 7.8s per sample).
Gemini 2.5 Pro vs Gemini 3.1 Pro Comparison Table
Evals updated August 20, 2026Pricing updated August 23, 2026
| 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 |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| 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, pooled at low effort | ||
| Overall | 66.0% | 83.1% |
| Avg cost / sample | $0.0050 | $0.0093 |
| Avg speed / sample | 6.11s | 7.81s |
| By task | ||
| Object Detection | 33.7% $0.010 | 67.4% $0.010 |
| Counting | 52.7% $0.0012 | 71.6% $0.0071 |
| Identification | 93.8% $0.0012 | 100.0% $0.0070 |
| OCR | 88.8% $0.0047 | 92.6% $0.0066 |
| Data Extraction | 84.5% $0.0013 | 94.8% $0.0063 |
| Reasoning (low) | 42.4% $0.0013 | 72.2% $0.012 |
| Reasoning (high) | 62.3% $0.011 | 74.8% $0.021 |
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.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.1 Pro performed better. It scores higher on all six vision tasks and averages 83.1% (#4 of 31) against 66.0% (#22 of 31) for Gemini 2.5 Pro. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark, Gemini 3.1 Pro leads with 67.4% against 33.7%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 2.5 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0050 per sample against $0.0093. Gemini 2.5 Pro is priced at $1.25 per 1M input tokens and $10.00 per 1M output; Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 2.5 Pro is faster. Across Roboflow's Vision Evals it averaged 6.1s per inference against 7.8s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.