GPT-5.6 Terra vs SAM 3
Compare GPT-5.6 Terra and SAM 3 side-by-side. See how these vision models stack up in Object Detection.
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GPT-5.6 Terra vs SAM 3 Comparison Table
Evals updated October 8, 2026Pricing updated October 11, 2026
| Property | GPT-5.6 Terra | SAM 3 |
|---|---|---|
| Organization | OpenAI | Meta |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Nov 2025 |
| Context Window | 1.1M | — |
| Parameters | Unknown | Unknown |
| License | Proprietary | Custom |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | No published price |
| Output $/1M | $12.00 | No published price |
| Vision Tasks | ||
| Object Detection | Demo | Demo |
| Captioning | Demo | Not listed |
| Chart Question Answering | Supported | Not listed |
| Classification | Demo | Not listed |
| Document Question Answering | Supported | Not listed |
| Image Tagging | Supported | Not listed |
| Instance Segmentation | Not listed | Supported |
| Multi-Label Classification | Supported | Not listed |
| OCR | Demo | Not listed |
| Open Vocabulary Object Detection | Not listed | Supported |
| Promptable Concept Segmentation | Not listed | Demo |
| Video Object Tracking | Not listed | Supported |
| Vision Language | Supported | Not listed |
| Visual Question Answering | Demo | Not listed |
| Zero Shot Segmentation | Not listed | Supported |
| Model Features | ||
| Foundation Vision | Supported | Supported |
| Multimodal Vision | Supported | Supported |
| LLMs with Vision Capabilities | Supported | Not listed |
| Zero-shot Detection | Not listed | Supported |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 66.0% | Not evaluated |
| Avg cost / sample | $0.010 | – |
| Avg speed / sample | 9.52s | – |
| By task | ||
| Object Detection (low) | 60.6% ±0.2, Mean of 3 runs, range 60.3 to 60.7 | – |
| Object Detection (high) | 61.3% ±0.4, Mean of 3 runs, range 60.8 to 61.6 | – |
| Counting (low) | 65.8% ±2.0, Mean of 3 runs, range 63.5 to 67.6 | – |
| Counting (high) | 62.6% ±2.7, Mean of 3 runs, range 59.5 to 64.9 | – |
| Identification (low) | 86.5% ±1.6, Mean of 3 runs, range 84.4 to 87.5 | – |
| Identification (high) | 86.5% ±3.1, Mean of 3 runs, range 84.4 to 90.6 | – |
| OCR (low) | 56.3% | – |
| by category |
| |
| OCR (high) | 56.9% | – |
| by category |
| |
| Reasoning (low) | 60.9% ±2.0, Mean of 3 runs, range 59.6 to 63.6 | – |
| Reasoning (high) | 65.3% ±1.0, Mean of 3 runs, range 64.2 to 66.2 | – |
GPT-5.6 Terra vs SAM 3: Overview
GPT-5.6 Terra is the mid-tier reasoning model in OpenAI's GPT-5.6 family, which also includes the flagship Sol and the lightweight Luna. Introduced in a limited preview on June 26, 2026, and made broadly available on July 9, 2026, Terra accepts text and image input and produces text output, supporting vision, function calling, tool use, and agentic workflows. It is designed as a balanced option for everyday professional and production workloads — including coding assistance, document analysis, customer support, and multi-step agent tasks — where both output quality and cost efficiency matter. OpenAI positions Terra as delivering performance competitive with GPT-5.5 at approximately half the price, with a context window of around 1,050,000 tokens. On Terminal-Bench 2.1, Terra scores 84.3%, matching Claude Fable 5 on that benchmark. Under OpenAI's Preparedness Framework, Terra is rated High for cybersecurity and biological capabilities, meaning it demonstrates meaningful capability in those domains without reaching the Critical threshold.
GPT-5.6 introduces a new naming convention in which the generation number (5.6) is paired with a durable capability tier name (Sol, Terra, or Luna), allowing each tier to advance on its own schedule. Terra carries the API identifier gpt-5.6-terra and supports the same reasoning effort controls available across the family, including adjustable reasoning depth. The model includes prompt caching with explicit cache breakpoints and a 30-minute minimum cache life, with cache writes billed at 1.25x the uncached input rate and cache reads receiving a 90% discount. GPT-5.6 Terra is a proprietary, closed-weights model served through the OpenAI API, Codex, and ChatGPT.
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.
GPT-5.6 Terra is released under Proprietary, while SAM 3 uses Custom. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
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.
