Gemini 2.5 Pro vs Grounded SAM
Compare Gemini 2.5 Pro and Grounded SAM side-by-side.
Compare Gemini 2.5 Pro vs Grounded SAM live
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Gemini 2.5 Pro vs Grounded SAM Comparison Table
Evals updated July 10, 2026Pricing updated July 16, 2026
| Property | Gemini 2.5 Pro | Grounded SAM |
|---|---|---|
| Organization | IDEA Research | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jun 2025 | Jan 2024 |
| Context Window | 1.0M | — |
| Parameters | ||
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $1.25 | |
| Output $/1M | $10.00 | |
| Vision Tasks | ||
| Vision Language | ||
| Captioning | Demo | |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | |
| Visual Question Answering | Demo | |
| Zero Shot Segmentation | ||
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| 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 Grounded SAM: 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.
Grounded SAM is an open-vocabulary image segmentation model developed by IDEA Research, released in January 2024 under the Apache 2.0 license. It combines Grounding DINO, a zero-shot open-vocabulary object detector, with the Segment Anything Model to produce precise segmentation masks for objects identified through free-form text prompts. The two models are used sequentially: Grounding DINO localizes objects from a text query, and SAM generates the corresponding segmentation masks.
Grounded SAM enables zero-shot instance segmentation without task-specific training data, making it applicable to domains where labeled segmentation data is scarce. It supports arbitrary text queries and can segment objects not represented in standard training sets. The model is commonly used in automated labeling pipelines, robotic perception, and domain-specific vision applications requiring open-vocabulary segmentation.