GPT-4.1 mini vs SAM 3
Compare GPT-4.1 mini and SAM 3 side-by-side. See how these vision models stack up in Object Detection.
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GPT-4.1 mini is deprecated and can no longer be run. Details and evals are still available on its model page.
Models in this comparison
GPT-4.1 mini vs SAM 3: Overview
GPT-4.1 mini, released by OpenAI in April 2025, is a smaller, faster, and cheaper variant of GPT-4.1 designed for high-throughput and cost-sensitive applications. It is multimodal, handling both text and images, and inherits the full model’s strengths in coding, structured outputs, and long-context reasoning. With support for up to 1 million tokens, it enables reliable processing of extended documents, multi-file codebases, and lengthy conversations while keeping latency low.
GPT-4.1 mini offers an efficient alternative to GPT-4.1 and replaced GPT-4o mini as the default ChatGPT model in May 2025. Despite being smaller, it matches or outperforms GPT-4o on several benchmarks, particularly for instruction following and real-world coding tasks. Ideal use cases include large-scale conversational systems, affordable developer tools, document analysis, and interactive assistants where speed and cost are critical.
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 mini vs SAM 3 Comparison Table
| Property | GPT-4.1 mini | 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 | $0.400 | |
| Output $/1M | $1.60 | |
| 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 | ||