GPT-4.1 nano vs SAM 3
Compare GPT-4.1 nano and SAM 3 side-by-side. See how these vision models stack up in Object Detection.
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GPT-4.1 nano is deprecated and can no longer be run. Details and evals are still available on its model page.
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GPT-4.1 nano vs SAM 3: Overview
GPT-4.1 nano, released by OpenAI in April 2025, is the smallest and most cost-efficient member of the GPT-4.1 family. It is multimodal, supporting both text and image inputs, and retains the family’s extended 1 million-token context window—allowing it to handle large documents or codebases despite its lightweight design. Its training knowledge extends to June 2024.
GPT-4.1 nano prioritizes speed and affordability over raw reasoning power. While less capable than GPT-4.1 and GPT-4.1 mini, it is well-suited for high-volume or latency-sensitive workloads such as classification, autocomplete, content moderation, and lightweight assistants. This makes it an attractive option for developers seeking scalable deployment where efficiency is more critical than deep reasoning.
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.
GPT-4.1 nano vs SAM 3 Comparison Table
| Property | GPT-4.1 nano | SAM 3 |
|---|---|---|
| Organization | OpenAI | Meta |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Apr 2025 | Nov 2025 |
| Context Window | 1.0M | — |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.100 | |
| Output $/1M | $0.400 | |
| Vision Tasks | ||
| Object Detection | Demo | |
| Captioning | ||
| Classification | ||
| Instance Segmentation | ||
| OCR | ||
| Promptable Concept Segmentation | Demo | |
| Video Object Tracking | ||
| Vision Language | ||
| Visual Question Answering | ||
| Zero Shot Segmentation | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
| Zero-shot Detection | ||