Claude Sonnet 4.5 vs Grounded SAM
Compare Claude Sonnet 4.5 and Grounded SAM side-by-side.
Compare Claude Sonnet 4.5 vs Grounded SAM live
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These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Claude Sonnet 4.5 vs Grounded SAM: Overview
Claude Sonnet 4.5, released by Anthropic in September 2025, is the company’s most advanced Sonnet-series model, built for high-performance reasoning, coding, and long-horizon agentic workflows. It is a multimodal system that accepts both text and images, with a 200,000-token context window designed for handling large documents and extended interactions. Anthropic highlights its improvements in reliability, reduced sycophancy, and alignment, making it suitable for sustained enterprise use.
The model delivers strong results in coding and autonomous workflows, achieving 61.4% on the OSWorld benchmark and leading performance on SWE-bench Verified. It introduces infrastructure features such as a memory tool (beta), checkpointing for Claude Code, parallel tool use, and tighter integration with VS Code. Compared to Opus, which targets broader reasoning, Sonnet 4.5 is optimized for structured, long-duration tasks. Positioned against leading offerings from OpenAI and Google, it is aimed at enterprise automation, software engineering, and research-intensive applications.
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.
Claude Sonnet 4.5 vs Grounded SAM Comparison Table
| Property | Claude Sonnet 4.5 | Grounded SAM |
|---|---|---|
| Organization | Anthropic | IDEA Research |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Sep 2025 | Jan 2024 |
| Context Window | 200K | — |
| Parameters | ||
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $3.00 | |
| Output $/1M | $15.00 | |
| 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 | ||