GPT-5.6 Sol vs SAM 3
GPT-5.6 Sol: 72.4% average across five Vision Evals tasks (#19 of 65 models). We have not run SAM 3 through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
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GPT-5.6 Sol vs SAM 3 Comparison Table
Evals updated October 26, 2026Pricing updated November 8, 2026
| Property | GPT-5.6 Sol | SAM 3 |
|---|---|---|
| Organization | OpenAI | Meta |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Nov 2025 |
| Context Window | 1.5M | — |
| Parameters | Unknown | Unknown |
| License | Proprietary | Custom |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $4.00 | No published price |
| Output $/1M | $20.00 | No published price |
| Vision Tasks | ||
| 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 |
Both support 1 more task | ||
| Model Features | ||
| LLMs with Vision Capabilities | Supported | Not listed |
| Zero-shot Detection | Not listed | Supported |
Both support 2 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 72.4% | Not evaluated |
| Avg cost / sample | $0.019 | – |
| Avg speed / sample | 12.16s | – |
| By task | ||
| Object Detection (low) | 68.4% ±0.7, Mean of 3 runs, range 67.9 to 69.3 | – |
| Object Detection (high) | 68.4% ±0.8, Mean of 3 runs, range 67.7 to 69.3 | – |
| Counting (low) | 74.3% ±1.4, Mean of 3 runs, range 73.0 to 75.7 | – |
| Counting (high) | 76.1% ±2.0, Mean of 3 runs, range 74.3 to 78.4 | – |
| Identification (low) | 89.6% ±4.7, Mean of 3 runs, range 84.4 to 93.8 | – |
| Identification (high) | 92.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 | – |
| OCR (low) | 63.6% | – |
| by category |
| |
| OCR (high) | 65.3% | – |
| by category |
| |
| Reasoning (low) | 66.0% ±2.6, Mean of 3 runs, range 63.6 to 68.9 | – |
| Reasoning (high) | 71.7% ±1.3, Mean of 3 runs, range 70.2 to 72.8 | – |
GPT-5.6 Sol vs SAM 3: Overview
GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, which also includes Terra (a balanced everyday-work tier) and Luna (a fast, cost-efficient tier). Sol is designed for demanding reasoning, long-horizon agentic workflows, software engineering, computer use, scientific research, and cybersecurity tasks. It introduces two new capability modes: a "max" reasoning effort setting that allocates additional compute time for difficult problems, and an "ultra" mode that coordinates multiple subagents in parallel to accelerate complex, multi-step work. The model supports native multimodal input, allowing it to process screenshots, diagrams, charts, documents, and photographs alongside text. A reported context window of approximately 1.5 million tokens enables processing of large codebases, lengthy research documents, and extended agentic sessions.
GPT-5.6 Sol was announced on June 26, 2026, initially in a limited preview for trusted partners, and reached general availability on July 9, 2026. On the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields, Sol scores 53.6. The model also demonstrates gains in life sciences evaluations, including long-horizon genomics and quantitative biology analyses. OpenAI paired the release with its most extensive safety evaluation to date, combining human red teaming with large-scale automated testing, and classified Sol as High capability in both cybersecurity and biological risk under its Preparedness Framework, though it does not cross the Critical threshold in either category.
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
GPT-5.6 Sol is released under Proprietary, while SAM 3 uses Custom. In practice: GPT-5.6 Sol: commercial use per vendor terms. 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.
