Gemini 2.5 Pro vs SAM 3
Compare Gemini 2.5 Pro and SAM 3 side-by-side. See how these vision models stack up in Object Detection.
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Gemini 2.5 Pro vs SAM 3 Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Gemini 2.5 Pro | SAM 3 |
|---|---|---|
| Organization | Meta | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 2025 | Nov 2025 |
| Context Window | 1.0M | — |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | |
| Output $/1M | $10.00 | |
| Vision Tasks | ||
| Object Detection | Demo | Demo |
| Captioning | Demo | |
| Classification | Demo | |
| Instance Segmentation | ||
| OCR | Demo | |
| Promptable Concept Segmentation | Demo | |
| Video Object Tracking | ||
| Vision Language | ||
| Visual Question Answering | Demo | |
| Zero Shot Segmentation | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Zero-shot Detection | ||
Vision Evalsground-truth scores across 6 vision tasks | ||
| Overall | 67.9% | Not evaluated |
| Object Detection | 26.4% | – |
| Counting | 52.7% | – |
| Identification | 93.8% | – |
| OCR | 88.8% | – |
| Data Extraction | 84.5% | – |
| Reasoning | 60.9% | – |
| Avg cost / sample | $0.0036 | – |
| Avg speed / sample | 4.7s | – |
Gemini 2.5 Pro vs SAM 3: 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.
Released on November 19th, 2025, Segment Anything 3 (SAM 3) is a zero-shot image segmentation model that “detects, segments, and tracks objects in images and videos based on concept prompts.” This model was developed by Meta as the third model in the Segment Anything series.
Unlike its previous SAM models (Segment Anything and Segment Anything 2), you can provide SAM 3 with the prompt “shipping container” and it will generate precise segmentation masks for all shipping containers in an image. SAM 3 generates segmentation masks that correspond to the location of the objects found with a text prompt.
Frequently Asked Questions
SAM 3 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.
